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EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance

ecosis · NIR

EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance. Origin database composed from 2 standardized v2.0 leaves: 2 spectral source(s), 51 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2ecosis
1,971
samples
4,002
wavelengths
2
sources
51
targets
30
metadata
NIR
family

Provenance & citation

Where the original data and publications come from. Follow these links to obtain the source and cite its authors. Reading guide

ContributorCABO 2018-2019 Leaf-Level Spectra v2
Conversion statuspartial
Origin · url [open]https://data.ecosis.org/dataset/cabo-2018-2019-leaf-level-spectra-v2
Origin · zenodo [open]10.5281/zenodo.10735410 — Zenodo
Publication10.1111/1365-2745.13972 — Plant spectra as integrative measures of phenotypes
Publication10.1111/nph.18713 — Predicting leaf traits across functional groups using reflectance spectroscopy
Publication10.5683/SP3/NYABAG — Models for Predicting leaf traits across functional groups using reflectance spectroscopy
Publication10.21232/58kApoRy — CABO 2018-2019 Leaf-Level Spectra v2
Publication10.1016/j.rse.2023.113926
Publication10.1080/00103624.2016.1228952
Publication10.1186/s13007-021-00816-4
Publication10.17504/protocols.io.q26g7rn23vwz/v2
Publication10.21232/44vxHorW
Publication10.21232/44vxhorw
Publication10.21232/deP7jVyq
Publication10.21232/dep7jvyq

Governance & integrity

Source license, redistribution conditions, content version and identity hashes. Redistribution tier and original-source availability are separate. Reading guide

Tierpublic
LicenseCC-BY-4.0
Permitted useResearch and benchmarking.
Access policyOpen per source license.
RedistributionEcoSIS CKAN metadata exposes an open license.
Content version1.1.0
Schema / protocol2.0
Content hash3dd80877f78b08f7…
Processing hash82cf51508ec0f8fe…
Metadata hash4e108b6c7570b81c…

Dataset property explorer

Start with the profile axes to locate unusual variation, then inspect the measured values and evidence below. Scores are descriptive heuristics. Reading guide

Mean available profile score0.55
Highest axisLocal artifacts · 1.00
Diagnostics8
Sources profiled2

How to read the profile

The center is 0 and the outer ring is 1. Larger values indicate stronger anomaly or heterogeneity signals on that axis. Compare individual axes using the table; this is not an overall quality grade. Missing axes are left blank, and partial profiles have no filled polygon.

EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureEcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance — integrity: 0.00EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance — noise: 0.00EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance — artefacts: 1.00EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance — baseline: 0.42EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance — PCA outliers: 0.63EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance — reference: 0.85EcoSIS CABO 2018-2019 leaf-level spectra v2, reflectance and transmittance — structure: 0.95EcoSIS CABO 201…0 center · 1 outer ring · outward = stronger anomaly / heterogeneity signal

Profile axes

Dimensionless scores from 0 to 1 summarize each property; larger values indicate stronger signals. Unavailable axes are not zero.

Integrity
?Combines missing cells, zero columns and infinite values. Higher values call for checking data completeness.
0.00
Noise
?Combines roughness and its signal-to-roughness proxy. Real narrow bands may also contribute.
0.00
Local artifacts
?Combines spike, jump and clipping heuristics. Inspect flagged spectral regions before attributing a cause.
1.00
Baseline/shape
?Summarizes baseline slope and excess edge variation relative to signal scale.
0.42
PCA outliers
?Combines relative PCA residual and score-distance tails. Valid rare spectra can produce a high value.
0.63
Distance to average spectrum
?Dispersion around this dataset's mean spectrum, using distance, shape and shift summaries.
0.85
Repeatability
?Dispersion among observations sharing an ID. Interpretation depends on the documented meaning of that ID.
unavailable
Multi-regime structure
?Variation in local density in PCA space. May reflect legitimate batches or subpopulations.
0.95

Possible explanations to investigate

Bars rank heuristic signatures from 0 to 1. They do not estimate the probability of a physical fault. On narrow screens, scroll the chart horizontally. Full labels, scores, evidence coverage, possible causes and required external checks are in the table below.

Diagnostic hypotheses00.250.50.751hypothesis scoreSignature compatible with a spectral spliceSignature compatible with a spectral splice: 0.860.86Signature compatible with a population shiftSignature compatible with a population shift: 0.640.64Offset compatible with a different white referenceOffset compatible with a different white reference: 0.530.53Signature compatible with a different backgroundSignature compatible with a different background: 0.480.48High spectral roughness signatureHigh spectral roughness signature: 0.370.37Signature compatible with clippingSignature compatible with clipping: 0.320.32Flat spectrum/weak signalFlat spectrum/weak signal: 0.120.12

Heuristic signature scores are not calibrated probabilities of physical causes: 0.78 does not mean a 78% causal probability. Missing evidence remains unavailable. RMS/SAM describe dispersion around the dataset mean, without an independent external reference.

Diagnostic hypotheses and supporting evidence
DiagnosticScoreHeuristic strengthEvidence coverageSignalsPossible causeRequired external checks
Signature compatible with a spectral spliceX_transmittance0.86strong100 %Spike rate 1.00, Jump rate 1.00, RMS/SAM to mean spectrum 1.00Break at detector junctions, local calibration or different probe.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Signature compatible with a population shiftX_transmittance0.64medium100 %RMS/SAM to mean spectrum 1.00, PCA structure 0.99, Mahalanobis / T2 0.75Different but physically plausible variety, species, batch or condition.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Offset compatible with a different white referenceX_transmittance0.53medium100 %RMS/SAM to mean spectrum 1.00, local artifacts 1.00, Mahalanobis / T2 0.75Systematic discrepancy between campaigns, instruments or white reference.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Signature compatible with a different backgroundX_transmittance0.48medium100 %RMS/SAM to mean spectrum 1.00, Mahalanobis / T2 0.75, PCA Q 0.62Systematic effect of support, white/black, transflectance or measurement environment.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
High spectral roughness signatureX_transmittance0.37weak100 %Spike rate 1.00, RMS/SAM to mean spectrum 1.00, PCA Q 0.62Weak signal, detector problem, lamp or unstable acquisition.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Signature compatible with clippingX_reflectance0.32weak100 %Jump rate 1.00, Baseline/mean/area 0.59, PCA Q 0.42Detector saturated or insufficient dynamic range.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Flat spectrum/weak signalX_transmittance0.12weak100 %PCA Q 0.62Bad contact, missing sample, degraded measurement or very low dynamic range.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Weak signatures observedX_reflectance—unknown90 %Weak signatures on available metrics; does not certify either physical validity or the absence of defects.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.

Spectral sources

Each block is a separate instrument or spectral source. Read its signal summary before using PCA to explore variation between observations. Reading guide

Source coverage
SourceObservationsSample units
ref_spec.csv1,9711,971
trans_spec.csv1,9711,971

1,971 sample units are measured by every source; 0 by a single source. Sources are joined by declared sample identity, never by row position.

ref_spec.csv

X_reflectance · NIR · Spectra Vista Corporation HR-1024i

Read the signal and variation summaries for this source. Axis unit: nm; signal representation: absorbance.

Spectral signal summary

The mean and median describe the typical signal at each channel; shaded bands show the 25th–75th and 5th–95th percentiles across observations. A wider band means greater variation, which can be biological or instrumental.

ref_spec.csv spectra0.00.20.40.605001,0001,5002,0002,500q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm400nm — median 0.04079 (q25–q75 0.03624–0.04565)414nm — median 0.04222 (q25–q75 0.03729–0.04836)429nm — median 0.04448 (q25–q75 0.03923–0.05282)443nm — median 0.04588 (q25–q75 0.04027–0.05512)458nm — median 0.04713 (q25–q75 0.0412–0.05708)472nm — median 0.04752 (q25–q75 0.04135–0.05758)486nm — median 0.04815 (q25–q75 0.04169–0.05826)501nm — median 0.05185 (q25–q75 0.04415–0.0631)515nm — median 0.06913 (q25–q75 0.05624–0.08468)529nm — median 0.1059 (q25–q75 0.08612–0.1275)544nm — median 0.1239 (q25–q75 0.1012–0.1488)558nm — median 0.1254 (q25–q75 0.102–0.1517)573nm — median 0.1032 (q25–q75 0.08092–0.1258)587nm — median 0.08661 (q25–q75 0.06671–0.1062)601nm — median 0.08076 (q25–q75 0.06197–0.09893)616nm — median 0.07082 (q25–q75 0.05491–0.08636)630nm — median 0.06623 (q25–q75 0.05181–0.08044)645nm — median 0.05949 (q25–q75 0.04751–0.07115)659nm — median 0.05311 (q25–q75 0.04421–0.06248)673nm — median 0.04958 (q25–q75 0.04339–0.05773)688nm — median 0.05883 (q25–q75 0.05076–0.06856)702nm — median 0.1401 (q25–q75 0.1174–0.1679)717nm — median 0.2822 (q25–q75 0.258–0.3126)731nm — median 0.3911 (q25–q75 0.3684–0.4147)745nm — median 0.444 (q25–q75 0.4216–0.4655)760nm — median 0.4607 (q25–q75 0.436–0.4809)774nm — median 0.4624 (q25–q75 0.4378–0.483)788nm — median 0.4622 (q25–q75 0.4376–0.483)803nm — median 0.4618 (q25–q75 0.4374–0.4829)817nm — median 0.4615 (q25–q75 0.4377–0.4826)832nm — median 0.4616 (q25–q75 0.438–0.4826)846nm — median 0.462 (q25–q75 0.4385–0.4829)860nm — median 0.4625 (q25–q75 0.4389–0.4831)875nm — median 0.4626 (q25–q75 0.4391–0.4833)889nm — median 0.4624 (q25–q75 0.4391–0.4827)904nm — median 0.4619 (q25–q75 0.4388–0.4823)918nm — median 0.4613 (q25–q75 0.4383–0.4818)932nm — median 0.4602 (q25–q75 0.4372–0.4804)947nm — median 0.4577 (q25–q75 0.4347–0.4775)961nm — median 0.4542 (q25–q75 0.4312–0.4736)976nm — median 0.4526 (q25–q75 0.4302–0.4719)990nm — median 0.452 (q25–q75 0.4303–0.4714)1,004nm — median 0.4513 (q25–q75 0.4301–0.4709)1,019nm — median 0.4531 (q25–q75 0.4314–0.4724)1,033nm — median 0.4556 (q25–q75 0.4333–0.475)1,047nm — median 0.4566 (q25–q75 0.4341–0.4763)1,062nm — median 0.4574 (q25–q75 0.4348–0.4771)1,076nm — median 0.4574 (q25–q75 0.4346–0.4772)1,091nm — median 0.4567 (q25–q75 0.4341–0.4764)1,105nm — median 0.4557 (q25–q75 0.4335–0.4751)1,119nm — median 0.4542 (q25–q75 0.432–0.4737)1,134nm — median 0.4497 (q25–q75 0.4283–0.4685)1,148nm — median 0.441 (q25–q75 0.4199–0.4588)1,163nm — median 0.4339 (q25–q75 0.4126–0.451)1,177nm — median 0.4318 (q25–q75 0.4105–0.4489)1,191nm — median 0.4303 (q25–q75 0.4092–0.4474)1,206nm — median 0.4303 (q25–q75 0.409–0.4473)1,220nm — median 0.4315 (q25–q75 0.4107–0.4487)1,235nm — median 0.4337 (q25–q75 0.4123–0.4508)1,249nm — median 0.4346 (q25–q75 0.4133–0.4519)1,263nm — median 0.4347 (q25–q75 0.4135–0.4518)1,278nm — median 0.4339 (q25–q75 0.413–0.451)1,292nm — median 0.4318 (q25–q75 0.411–0.4485)1,306nm — median 0.4278 (q25–q75 0.4069–0.4441)1,321nm — median 0.4189 (q25–q75 0.399–0.4358)1,335nm — median 0.4074 (q25–q75 0.3872–0.4244)1,350nm — median 0.3937 (q25–q75 0.3734–0.4113)1,364nm — median 0.3812 (q25–q75 0.3597–0.3986)1,378nm — median 0.3582 (q25–q75 0.3343–0.3766)1,393nm — median 0.2991 (q25–q75 0.2702–0.3225)1,407nm — median 0.2332 (q25–q75 0.205–0.2581)1,422nm — median 0.1964 (q25–q75 0.1686–0.222)1,436nm — median 0.1838 (q25–q75 0.1558–0.2085)1,450nm — median 0.1823 (q25–q75 0.1542–0.2069)1,465nm — median 0.1884 (q25–q75 0.1596–0.2126)1,479nm — median 0.2002 (q25–q75 0.1713–0.2247)1,494nm — median 0.2178 (q25–q75 0.1887–0.2428)1,508nm — median 0.2355 (q25–q75 0.2069–0.2605)1,522nm — median 0.2524 (q25–q75 0.2243–0.2766)1,537nm — median 0.2688 (q25–q75 0.2416–0.2915)1,551nm — median 0.2819 (q25–q75 0.2561–0.3038)1,565nm — median 0.2937 (q25–q75 0.2681–0.3141)1,580nm — median 0.3035 (q25–q75 0.2788–0.3228)1,594nm — median 0.3112 (q25–q75 0.2869–0.3304)1,609nm — median 0.3185 (q25–q75 0.2944–0.3371)1,623nm — median 0.3239 (q25–q75 0.3003–0.3418)1,637nm — median 0.3276 (q25–q75 0.3051–0.345)1,652nm — median 0.3294 (q25–q75 0.3079–0.3471)1,666nm — median 0.3296 (q25–q75 0.3083–0.3472)1,681nm — median 0.3277 (q25–q75 0.3068–0.3452)1,695nm — median 0.3241 (q25–q75 0.3032–0.3414)1,709nm — median 0.319 (q25–q75 0.2975–0.3366)1,724nm — median 0.3137 (q25–q75 0.292–0.3314)1,738nm — median 0.3083 (q25–q75 0.2858–0.3261)1,753nm — median 0.3016 (q25–q75 0.2787–0.3197)1,767nm — median 0.2951 (q25–q75 0.2717–0.3138)1,781nm — median 0.2904 (q25–q75 0.2669–0.3094)1,796nm — median 0.2887 (q25–q75 0.2649–0.3076)1,810nm — median 0.2889 (q25–q75 0.265–0.3078)1,824nm — median 0.2891 (q25–q75 0.2652–0.3079)1,839nm — median 0.2863 (q25–q75 0.2616–0.3051)1,853nm — median 0.2734 (q25–q75 0.248–0.2936)1,868nm — median 0.2366 (q25–q75 0.211–0.2585)1,882nm — median 0.1744 (q25–q75 0.1476–0.1988)1,896nm — median 0.1045 (q25–q75 0.0869–0.1212)1,911nm — median 0.06771 (q25–q75 0.05591–0.07956)1,925nm — median 0.05426 (q25–q75 0.04521–0.06433)1,940nm — median 0.0532 (q25–q75 0.04432–0.06291)1,954nm — median 0.05808 (q25–q75 0.04809–0.06881)1,968nm — median 0.06595 (q25–q75 0.05359–0.07819)1,983nm — median 0.07609 (q25–q75 0.06093–0.09066)1,997nm — median 0.08545 (q25–q75 0.06804–0.1017)2,012nm — median 0.09673 (q25–q75 0.07729–0.1147)2,026nm — median 0.1069 (q25–q75 0.08621–0.126)2,040nm — median 0.1167 (q25–q75 0.09457–0.1358)2,055nm — median 0.1257 (q25–q75 0.1032–0.1449)2,069nm — median 0.1331 (q25–q75 0.1107–0.1527)2,083nm — median 0.1402 (q25–q75 0.1179–0.16)2,098nm — median 0.1475 (q25–q75 0.1251–0.1672)2,112nm — median 0.154 (q25–q75 0.1314–0.1738)2,127nm — median 0.16 (q25–q75 0.1376–0.1801)2,141nm — median 0.1652 (q25–q75 0.1428–0.185)2,155nm — median 0.1695 (q25–q75 0.1472–0.1897)2,170nm — median 0.1736 (q25–q75 0.1517–0.1941)2,184nm — median 0.1775 (q25–q75 0.1556–0.1982)2,199nm — median 0.1812 (q25–q75 0.1595–0.2017)2,213nm — median 0.1832 (q25–q75 0.1613–0.2035)2,227nm — median 0.1822 (q25–q75 0.1603–0.2025)2,242nm — median 0.1784 (q25–q75 0.1562–0.1982)2,256nm — median 0.1715 (q25–q75 0.1492–0.1909)2,271nm — median 0.1625 (q25–q75 0.1401–0.1816)2,285nm — median 0.1539 (q25–q75 0.1315–0.1727)2,299nm — median 0.1462 (q25–q75 0.1236–0.1647)2,314nm — median 0.1387 (q25–q75 0.1159–0.1568)2,328nm — median 0.1321 (q25–q75 0.1099–0.1502)2,342nm — median 0.1255 (q25–q75 0.1041–0.1439)2,357nm — median 0.1188 (q25–q75 0.09779–0.137)2,371nm — median 0.1128 (q25–q75 0.09203–0.1304)2,386nm — median 0.1054 (q25–q75 0.08519–0.1224)2,400nm — median 0.09832 (q25–q75 0.07847–0.1149)

Sampling

How many observations and spectral channels were exported, and how the wavelength axis is spaced. Reading guide

Wavelengths
?Number of spectral channels. A channel can represent wavelength, wavenumber or another feature axis.
2,001
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
400–2,400 nm
Mean spacing
?Average difference between adjacent spectral-axis coordinates; compare only within the same unit.
1 nm
Grid
?Uniform means adjacent axis spacings are approximately equal. An irregular grid may need care when applying derivatives.
uniform
Observations
?Exported spectral rows in this source, including repeated measurements when present.
1,971

Signal & quality

Signal level and roughness summaries. These depend on the signal representation and are not instrument acceptance tests. Reading guide

Value range
?Minimum and maximum recorded spectral values, in the original signal representation.
0.0146 – 0.682
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
0.0415 – 0.46
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
0.2589
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
518
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
0.4183
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
1.2744e-05
Roughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR.
2e+04
Roughness S/N proxy dB
?20 log10 of the roughness signal-to-noise proxy. Units are decibels; compare only compatible signal representations.
9e+01 dB
Dynamic range
?Maximum minus minimum of the mean spectrum. Its magnitude depends on the signal representation.
0.418
Smoothness
?Mean per-spectrum RMS of second differences, in signal units. Smaller values indicate smoother spectra under this protocol.
0.000258
Saturated
?Fraction at the observed global maximum; a heuristic indicator, not a comparison with known detector limits.
0.0%
X-outliers
?Number flagged by the qualification outlier method. An unusual spectrum can be valid and should not be discarded automatically.
963

Integrity & artefacts

Missing values, narrow spikes and abrupt jumps to investigate in the original spectra. Reading guide

NaN ratio
?Missing spectral cells divided by all spectral cells, displayed as a percentage.
0.00%
Inf count
?Number of positive or negative infinite spectral values; investigate invalid calculations or export.
0
Zero ratio
?Exactly zero spectral cells divided by all cells. Zero can be a valid measurement and is not automatically missing.
0.00%
Spike count
?Local narrow peaks flagged by the second-difference heuristic; real sharp spectral bands may also be flagged.
101,895
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
2.59%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
152,162
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
3.86%
Clip fraction
?Fraction of finite cells near the observed global minimum or maximum; inspect detector limits before concluding saturation.
0.00%

Shape & reference

Variation relative to this dataset's mean spectrum; the mean is not an independently measured calibration reference. Reading guide

Baseline slope
?Linear slope fitted to the mean spectrum over an axis normalized to 0–1. It describes total baseline change, not change per physical axis unit.
-0.1226
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.00024887
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.0016296
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
0.025394
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
0.071626
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.055789
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.14769
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
0.053782
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
0.23937
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
0.034937
Xcorr lag p95
?95th percentile of the absolute cross-correlation shift relative to the mean spectrum, in spectral channels.
0

Outliers & repeatability

Unusual spectra and within-ID dispersion. Repeated IDs do not by themselves establish technical repetitions. Reading guide

PCA Q p95/median
?Q (squared prediction error) is variation left outside the retained PCA subspace. The displayed ratio compares its 95th percentile with its median.
3.4
Hotelling T2 p95/median
?Hotelling T² measures distance within the retained PCA subspace, scaled by component variance. Ratio of the 95th percentile to the median.
4.1
Mahalanobis H p95/median
?Distance from the PCA-score center after variance scaling. Ratio of the 95th percentile to the median; large values identify relatively extreme spectra.
2
Repeat groups
?Number of IDs with several observations. Source documentation is needed to decide whether these are technical repeats, positions or time points.
0

Dimensionality (PCA)

Principal component analysis (PCA) compresses correlated wavelengths into components. This describes spectral variation, without using prediction targets. Reading guide

Effective rank
?Entropy-based summary of the variance distribution across components. Larger values indicate variation spread across more dimensions.
2.5
PCs → 95% var
?Number of principal components needed to explain 95% of spectral variance, when reached by the computed projection.
3
PCs → 99% var
?Number of principal components needed to explain 99% of spectral variance, when reached by the computed projection.
6
Top-10 cum. var
?Fraction of spectral variance explained by up to the first ten computed principal components, displayed as a percentage.
99.8%
Computed metric scores 30highest alert 1.00

Value is the measured quantity; alert score is its heuristic mapping to 0–1. Levels are weak below 0.42, medium from 0.42, and strong from 0.72. These are display bands, not calibrated acceptance thresholds. A dash means unavailable, never zero. Possible causes are suggestions to investigate. Use each metric’s ? control for its meaning and scoring: hover for a hint, or expand it with a tap, Enter or Space.

FamilyComputed metricValueAlert scoreHeuristic levelDescriptive interpretationPossible causes to verifyCalculation / scoring
Data integrityInvalid/masked cell count (owner report)
?Count of cells reported unavailable by the native owner under its null or validity mask. This count is distinct from the historical NaN ratio; consult the recorded population and denominator. Scoring: No alert mapping is defined for this metric; an unavailable score does not mean a zero measured value. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.missing_cells		——not calculableNot enough information to score this metric on this dataset.Missing data or validity mask; not evidence of an acquisition causeNative Preflight count of cells unavailable under x/null and valid_mask; denominator stays in native_metric.denominators.n_cells. Not legacy NaN ratio.
Data integrityNaN ratio
?Missing spectral cells divided by all spectral cells, displayed as a percentage. Scoring: alert = min(1, nan_ratio / 0.05). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.nan_ratio		0%0.00weakFull spectrumAcquisition/export errorcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Data integrityInf count
?Number of positive or negative infinite spectral values; investigate invalid calculations or export. Scoring: alert = min(1, inf_count / 1). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.inf_count		00.00weakNormalInvalid calculationscount(isinf(X))alert = min(1, inf_count / 1)
Data integrityZero ratio
?Exactly zero spectral cells divided by all cells. Zero can be a valid measurement and is not automatically missing. Scoring: alert = min(1, zero_ratio / 0.05). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.zero_ratio		0%0.00weakNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Overall amplitudeMean reflectance
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations. Scoring: alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.mean_reflectance		0.258910.59mediumAtypical value: Too light / background visible or Too darkBackground, geometrymean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Overall amplitudeArea under curve
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit. Scoring: alert reuses baseline/shape drift because area scale depends on axis and units. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.area_under_curve		518.010.59mediumAtypical value: Illumination difference or NormalProbe distancetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Overall amplitudePeak-to-peak (PTP)
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum. Scoring: alert increases when dynamic range is abnormally flat. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.peak_to_peak		0.418280.00weakStrong variabilitySaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Overall amplitudeVariance
?Variance of all finite spectral cells, in squared signal units. It combines variation across observations and channels; a small value can describe a flat signal. Scoring: alert increases when variance/dynamic range is abnormally flat. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.variance		0.0231670.00weakNormal or heterogeneousBad contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
NoiseRoughness sigma proxy
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise. Scoring: alert = noise_rms / signal_scale, saturated at 5%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.roughness_sigma_proxy		1.2744e-050.00weakStableLamp, detectormedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
NoiseRoughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR. Scoring: alert decreases with SNR dB; >=40 dB is treated as low alert. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.roughness_signal_to_noise_proxy		203160.00weakGood signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
NoiseBandwise roughness S/N proxy
?Minimum channel-wise ratio of absolute mean signal to local second-difference roughness. A smaller ratio identifies a weak or rough spectral region; genuine narrow bands and near-zero signal can also lower it. This is not certified instrument SNR. Scoring: alert decreases with worst-band SNR dB; >=35 dB is treated as low alert. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.bandwise_roughness_signal_to_noise_proxy_min		107.720.00weakReliable zoneDetectormin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Local artifactsSpike count
?Local narrow peaks flagged by the second-difference heuristic; real sharp spectral bands may also be flagged. Scoring: alert follows spike_rate, saturated at 1%. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.spike_count		101,8951.00strongArtifactsCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Local artifactsSpike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage. Scoring: alert = min(1, spike_rate / 0.01). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.spike_rate		2.59%1.00strongSuspicious spectrumInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Local artifactsJump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins. Scoring: alert follows jump_rate, saturated at 1%. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.jump_count		152,1621.00strongDetector connectionSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Local artifactsJump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage. Scoring: alert = min(1, jump_rate / 0.01). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.jump_rate		3.86%1.00strongSpectral problemCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Local artifactsClip fraction
?Fraction of finite cells near the observed global minimum or maximum; inspect detector limits before concluding saturation. Scoring: alert = min(1, clip_fraction / 0.01). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.clip_fraction		5.07e-05%0.00weakNormalDetector saturatedfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Spectral formBaseline slope
?Linear slope fitted to the mean spectrum over an axis normalized to 0–1. It describes total baseline change, not change per physical axis unit. Scoring: alert = abs(slope / signal_scale), saturated at 0.5. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
shape.baseline_slope		-0.12260.59mediumDriftIlluminationlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Spectral formCurvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation. Scoring: alert = curvature_rms / signal_scale, saturated at 1%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
shape.curvature_rms		0.000248870.06weakSmoothBackground, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Spectral formD1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts. Scoring: alert = d1_rms / signal_scale, saturated at 5%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
shape.d1_rms		0.00162960.08weakFlatBiology or artifactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Multivariate outliersPCA Q (SPE)
?Q (squared prediction error) is variation left outside the retained PCA subspace. The displayed ratio compares its 95th percentile with its median. Scoring: alert = min(1, pca_q_ratio / 8). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.pca_q_ratio		3.3530.42weakCompliantArtifact, mixturep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Multivariate outliersHotelling T²
?Hotelling T² measures distance within the retained PCA subspace, scaled by component variance. Ratio of the 95th percentile to the median. Scoring: alert = min(1, hotelling_t2_ratio / 8). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.hotelling_t2_ratio		4.13020.52mediumExtreme but consistentNatural variabilityp95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Multivariate outliersMahalanobis H
?Distance from the PCA-score center after variance scaling. Ratio of the 95th percentile to the median; large values identify relatively extreme spectra. Scoring: alert = min(1, mahalanobis_h_ratio / 4). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.mahalanobis_h_ratio		2.03230.51mediumGlobal outlierDifferent domainp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparison to average spectrumRMS to mean spectrum
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value. Scoring: alert = RMS_p95 / signal_scale, saturated at 25%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
reference.rms_to_mean_spectrum_p95		0.0716260.68mediumDifferent spectrumDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparison to average spectrumSpectral Angle Mapper (SAM)
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS. Scoring: alert = min(1, SAM_p95 / 0.35 rad). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
reference.sam_to_mean_spectrum_p95		0.147690.42mediumDifferent shapeBackground, geometryp95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RepeatabilityRMS intra-ID
?Within-ID root mean square deviation from the group's mean spectrum, in signal units. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = RMS_intra_ID / signal_scale, saturated at 10%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.rms_intra_id		——not calculableNot enough information to score this metric on this dataset.Positioningmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RepeatabilitySAM intra-ID
?Within-ID spectral angle to the group's mean spectrum, in radians. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = min(1, SAM_intra_ID / 0.15 rad). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.sam_intra_id		——not calculableNot enough information to score this metric on this dataset.Acquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RepeatabilityCV intra-ID
?Within-ID coefficient of variation: standard deviation relative to absolute mean; unstable near zero signal. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = min(1, CV_intra_ID / 0.25). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.cv_intra_id		——not calculableNot enough information to score this metric on this dataset.Operatormedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure of the datasetPCA score density
?Inverse median distance to nearby observations in retained PCA-score space. Larger raw values mean more closely spaced observations; scale depends on the PCA representation. The alert uses density variation, so raw density alone does not establish an anomaly. Scoring: alert follows density_cv/profile structure complexity, not raw density alone. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.pca_score_density		4.06940.91strongSubpopulationsDifferent batches1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure of the datasetkNN distance ratio (not LOF)
?95th percentile of mean k-nearest-neighbor distance divided by the population median of that distance, in PCA-score space. Values above 1 indicate an upper tail with more isolated observations; valid rare spectra can also be isolated. This distance ratio is not the Local Outlier Factor algorithm. Scoring: alert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.knn_distance_ratio_p95		2.7320.87strongIsolated spectrumRare casesp95(mean kNN distance / median population mean kNN distance) in PCA-score space; not LOFalert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2)
Structure of the datasetIsolation Forest score
?95th percentile of the negated Isolation Forest score in retained PCA-score space. Larger raw scores indicate easier isolation under that model; the scale is implementation-dependent. The displayed alert reuses structure complexity rather than directly mapping this raw score. Scoring: alert follows structure complexity; raw score is implementation-dependent. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.isolation_forest_score_p95		0.570980.91strongAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source ref_spec.csv: 800 of 1,971 source observations are plotted. PC1 captures 66.5% and PC2 26.2% of the reported spectral variance: 92.7% together; 7.3% remains outside this view.

Principal component analysis (PCA) summarizes spectral differences without using targets. The horizontal PC1 axis captures the largest variation; vertical PC2 captures the next largest direction of variation. Each dot is one observation; repeated measurements need not be distinct samples. Scores are projection coordinates, not wavelengths or target values. Nearby dots have similar projections; separate groups or isolated dots are leads to inspect in the original spectra and acquisition metadata. Overlapping dots can differ in omitted dimensions. The dots have no class or batch labels, so this view cannot identify groups, confirm defective observations, explain a chemical cause or measure prediction accuracy.

ref_spec.csv PCA score plot-10-50510-4-2024PC1 -0.2484 · PC2 -0.0504PC1 0.4684 · PC2 -0.1541PC1 0.2036 · PC2 0.1426PC1 0.7166 · PC2 0.2674PC1 0.3779 · PC2 0.2377PC1 0.9857 · PC2 -0.05259PC1 0.9461 · PC2 -0.04984PC1 0.3622 · PC2 0.3021PC1 0.3566 · PC2 0.01941PC1 1.18 · PC2 0.4629PC1 1.005 · PC2 -0.02944PC1 0.5287 · PC2 0.3677PC1 1.234 · PC2 0.163PC1 -0.5245 · PC2 -0.2663PC1 1.099 · PC2 -0.1033PC1 0.5095 · PC2 0.1877PC1 0.2804 · PC2 0.3199PC1 0.1317 · PC2 0.9124PC1 0.1485 · PC2 0.3453PC1 0.09632 · PC2 0.2347PC1 0.09987 · PC2 0.3098PC1 0.3037 · PC2 0.8269PC1 0.5576 · PC2 0.7485PC1 0.09005 · PC2 0.5794PC1 -0.1336 · PC2 0.4106PC1 -0.5664 · PC2 -0.08666PC1 -0.4189 · PC2 -0.1743PC1 -0.5335 · PC2 -0.2919PC1 -0.4301 · PC2 -0.05238PC1 -0.3014 · PC2 -0.1134PC1 -0.369 · PC2 -0.1826PC1 0.3704 · PC2 0.3903PC1 0.4861 · PC2 0.345PC1 1.369 · PC2 0.6567PC1 0.7957 · PC2 0.02324PC1 1.117 · PC2 0.3017PC1 0.1782 · PC2 0.1839PC1 0.4917 · PC2 0.2392PC1 0.658 · PC2 0.04024PC1 0.6974 · PC2 0.09589PC1 0.7916 · PC2 -0.03833PC1 0.1879 · PC2 0.2322PC1 -0.1959 · PC2 -0.2611PC1 -0.1691 · PC2 0.4273PC1 -0.2805 · PC2 -0.0001523PC1 -0.4912 · PC2 -0.1345PC1 0.7309 · PC2 0.3344PC1 0.5486 · PC2 0.02875PC1 0.2949 · PC2 -0.2391PC1 0.849 · PC2 0.02266PC1 0.5827 · PC2 0.4023PC1 0.3845 · PC2 -0.1038PC1 -0.267 · PC2 -0.04306PC1 -0.03901 · PC2 -0.1443PC1 0.8476 · PC2 0.5269PC1 0.8513 · PC2 0.466PC1 0.3618 · PC2 0.916PC1 0.5561 · PC2 0.7274PC1 0.5881 · PC2 0.5414PC1 0.7568 · PC2 0.2879PC1 1.387 · PC2 0.2076PC1 1.118 · PC2 0.6769PC1 1.192 · PC2 0.7892PC1 -0.5206 · PC2 -0.5145PC1 -0.5059 · PC2 -0.3924PC1 0.5471 · PC2 0.1125PC1 0.551 · PC2 0.1736PC1 -0.06509 · PC2 -0.3291PC1 0.714 · PC2 -0.2585PC1 0.2383 · PC2 0.03697PC1 -0.04478 · PC2 0.4821PC1 0.04454 · PC2 0.9026PC1 -0.5943 · PC2 0.02823PC1 0.2174 · PC2 -0.02808PC1 -0.3819 · PC2 -0.5109PC1 0.2568 · PC2 0.09689PC1 0.4233 · PC2 -0.1259PC1 -0.7353 · PC2 -0.1544PC1 -0.4997 · PC2 -0.2672PC1 -0.7032 · PC2 -0.4816PC1 -0.1078 · PC2 -0.3002PC1 -0.4525 · PC2 -0.2323PC1 -0.9255 · PC2 0.459PC1 -0.7365 · PC2 0.4583PC1 -1.014 · PC2 0.129PC1 -0.9102 · PC2 0.07189PC1 -0.9365 · PC2 0.2551PC1 -0.5946 · PC2 0.4224PC1 0.03297 · PC2 -0.03772PC1 0.1513 · PC2 -0.6099PC1 0.4795 · PC2 -0.382PC1 0.07894 · PC2 -0.1125PC1 0.3529 · PC2 0.4475PC1 0.8154 · PC2 0.491PC1 1.279 · PC2 1.108PC1 0.5191 · PC2 0.6023PC1 0.6446 · PC2 0.9889PC1 0.5182 · PC2 0.2395PC1 1.208 · PC2 0.07156PC1 0.2369 · PC2 -0.3486PC1 0.1729 · PC2 0.01359PC1 0.3258 · PC2 -0.3026PC1 0.4995 · PC2 -0.03848PC1 -0.3154 · PC2 0.243PC1 -0.2811 · PC2 0.2081PC1 1.187 · PC2 0.6237PC1 1.342 · PC2 0.08701PC1 0.8858 · PC2 0.8104PC1 0.9865 · PC2 0.6785PC1 1.131 · PC2 0.8605PC1 -0.06434 · PC2 -0.1406PC1 0.9023 · PC2 0.3904PC1 -0.5035 · PC2 -0.5281PC1 0.5792 · PC2 0.3564PC1 1.085 · PC2 0.7323PC1 0.7716 · PC2 0.5353PC1 1.178 · PC2 0.3841PC1 1.747 · PC2 0.1299PC1 -0.2053 · PC2 -0.02162PC1 -0.05993 · PC2 -0.1323PC1 -0.5048 · PC2 0.004507PC1 -0.03465 · PC2 0.06109PC1 0.5166 · PC2 0.4851PC1 1.196 · PC2 0.6267PC1 1.177 · PC2 -0.3915PC1 0.6946 · PC2 -0.4763PC1 0.2528 · PC2 -0.2904PC1 0.5771 · PC2 -0.2109PC1 1.422 · PC2 1.108PC1 1.023 · PC2 1.068PC1 0.1373 · PC2 0.2772PC1 -0.0223 · PC2 -0.1024PC1 0.3327 · PC2 -0.1306PC1 0.7647 · PC2 -0.07376PC1 0.4455 · PC2 0.2066PC1 0.9468 · PC2 -0.06238PC1 1.36 · PC2 0.2663PC1 0.9195 · PC2 -0.3683PC1 1.164 · PC2 -0.06989PC1 0.2914 · PC2 0.05644PC1 0.5232 · PC2 -0.1202PC1 -0.2887 · PC2 -0.4559PC1 0.8353 · PC2 0.6343PC1 -0.2254 · PC2 -0.1014PC1 -0.2404 · PC2 -0.2807PC1 -0.2129 · PC2 -0.09842PC1 -0.1906 · PC2 -0.2283PC1 0.6374 · PC2 1.502PC1 1.63 · PC2 0.2606PC1 0.9944 · PC2 0.2835PC1 0.5051 · PC2 -0.1272PC1 -0.6713 · PC2 -0.3218PC1 0.171 · PC2 -0.3271PC1 0.8879 · PC2 0.4058PC1 0.7955 · PC2 0.3175PC1 1.757 · PC2 0.8915PC1 -0.6734 · PC2 -0.1319PC1 -0.3805 · PC2 -0.2371PC1 -0.2532 · PC2 -0.5052PC1 0.927 · PC2 0.4933PC1 1.492 · PC2 0.254PC1 0.8483 · PC2 1.151PC1 0.7987 · PC2 0.5297PC1 -0.6186 · PC2 -0.4679PC1 -0.3563 · PC2 -0.5602PC1 0.7039 · PC2 0.5167PC1 0.3667 · PC2 0.37PC1 1.725 · PC2 0.1436PC1 1.296 · PC2 0.6914PC1 1.128 · PC2 0.7487PC1 -0.256 · PC2 -0.1721PC1 -0.4668 · PC2 -0.4419PC1 1.042 · PC2 0.3PC1 -0.4957 · PC2 -0.2656PC1 -0.5304 · PC2 -0.4676PC1 -0.04458 · PC2 -0.1849PC1 -0.2821 · PC2 -0.587PC1 -4.983 · PC2 0.6294PC1 -3.954 · PC2 -0.01258PC1 -3.999 · PC2 1.1PC1 -0.2849 · PC2 0.4463PC1 0.7418 · PC2 1.342PC1 -1.106 · PC2 0.9696PC1 -1.728 · PC2 -0.2158PC1 -1.096 · PC2 -0.7852PC1 -3.502 · PC2 0.0692PC1 0.4968 · PC2 1.653PC1 0.6183 · PC2 1.575PC1 0.8755 · PC2 1.128PC1 0.6587 · PC2 2.092PC1 0.2945 · PC2 0.3766PC1 0.6379 · PC2 -0.1033PC1 0.8237 · PC2 0.8294PC1 -1.021 · PC2 0.7548PC1 0.515 · PC2 1.378PC1 1.079 · PC2 0.6694PC1 -3.589 · PC2 0.5262PC1 -4.576 · PC2 0.4286PC1 -0.2694 · PC2 0.1618PC1 1.11 · PC2 -0.4013PC1 0.9148 · PC2 -0.5964PC1 1.469 · PC2 1.004PC1 1.608 · PC2 0.2102PC1 1.472 · PC2 1.048PC1 0.9796 · PC2 0.5225PC1 -0.2514 · PC2 0.2128PC1 0.2736 · PC2 -0.5583PC1 0.2697 · PC2 0.6046PC1 0.4048 · PC2 0.07268PC1 1.207 · PC2 0.3093PC1 -2.293 · PC2 0.515PC1 -3.253 · PC2 0.6723PC1 -2.749 · PC2 -0.4141PC1 -2.269 · PC2 -0.5579PC1 -0.396 · PC2 0.2561PC1 0.7629 · PC2 0.84PC1 1.161 · PC2 1.191PC1 -0.9636 · PC2 0.1937PC1 0.656 · PC2 0.3549PC1 1.684 · PC2 1.446PC1 0.7619 · PC2 -0.1911PC1 0.5553 · PC2 -0.2288PC1 0.04937 · PC2 -0.006602PC1 -0.2888 · PC2 0.7176PC1 -0.563 · PC2 0.9252PC1 0.06063 · PC2 1.316PC1 -0.1977 · PC2 0.08259PC1 0.6923 · PC2 0.579PC1 -0.4708 · PC2 0.9378PC1 -0.4568 · PC2 0.501PC1 -0.2111 · PC2 -0.2886PC1 -0.7894 · PC2 -0.2215PC1 -0.02667 · PC2 0.2948PC1 -0.7441 · PC2 -0.4164PC1 -0.2257 · PC2 0.2645PC1 -0.1091 · PC2 0.2652PC1 1.101 · PC2 0.4383PC1 1.06 · PC2 0.003827PC1 1.274 · PC2 0.9447PC1 -1.089 · PC2 0.06622PC1 0.6197 · PC2 0.9842PC1 -0.5862 · PC2 -0.04006PC1 -0.8538 · PC2 1.489PC1 -0.4062 · PC2 0.4902PC1 1.317 · PC2 0.5497PC1 0.6524 · PC2 1.345PC1 0.8894 · PC2 1.383PC1 0.9651 · PC2 1.606PC1 -0.1181 · PC2 0.2885PC1 -0.5034 · PC2 0.4961PC1 -0.8454 · PC2 0.4237PC1 -0.0002989 · PC2 -0.1783PC1 -0.2718 · PC2 0.1759PC1 0.2055 · PC2 1.063PC1 0.2211 · PC2 1.115PC1 -0.05556 · PC2 1.028PC1 0.262 · PC2 1.23PC1 -0.00561 · PC2 0.7445PC1 0.7056 · PC2 1.022PC1 1.304 · PC2 0.9334PC1 0.3007 · PC2 1.505PC1 0.5242 · PC2 0.8221PC1 0.5938 · PC2 0.07657PC1 0.3687 · PC2 1.732PC1 0.8087 · PC2 -0.2623PC1 0.9242 · PC2 1.367PC1 1.105 · PC2 0.02396PC1 1.536 · PC2 0.4627PC1 1.307 · PC2 0.9399PC1 1.985 · PC2 1.227PC1 0.2853 · PC2 1.357PC1 1.236 · PC2 0.6923PC1 1.64 · PC2 1.457PC1 0.07099 · PC2 1.43PC1 0.1412 · PC2 1.444PC1 0.5261 · PC2 1.275PC1 0.1598 · PC2 1.13PC1 0.7725 · PC2 1.176PC1 0.9535 · PC2 1.48PC1 0.429 · PC2 1.367PC1 0.8461 · PC2 1.473PC1 -0.5684 · PC2 0.7858PC1 1.138 · PC2 0.8983PC1 0.5121 · PC2 0.2918PC1 0.5789 · PC2 -0.4198PC1 0.4097 · PC2 0.102PC1 -3.115 · PC2 0.4249PC1 -2.624 · PC2 0.5212PC1 0.9422 · PC2 0.2209PC1 1.74 · PC2 -0.8007PC1 -0.7359 · PC2 -0.02491PC1 -2.607 · PC2 0.367PC1 -2.219 · PC2 0.404PC1 -0.3559 · PC2 1.052PC1 -3.768 · PC2 -0.3139PC1 -0.184 · PC2 0.4086PC1 0.07875 · PC2 0.3PC1 -0.6545 · PC2 -0.02868PC1 1.187 · PC2 -2.146PC1 -0.6753 · PC2 -1.235PC1 0.6114 · PC2 -1.369PC1 -5.227 · PC2 0.6147PC1 0.02514 · PC2 0.839PC1 0.04954 · PC2 0.7094PC1 1.647 · PC2 0.7929PC1 1.752 · PC2 0.2781PC1 0.7432 · PC2 0.5949PC1 -1.192 · PC2 -0.03094PC1 0.8386 · PC2 2.237PC1 -0.4418 · PC2 0.8294PC1 0.4928 · PC2 1.52PC1 0.1876 · PC2 1.997PC1 -0.08708 · PC2 1.903PC1 0.2972 · PC2 1.749PC1 0.3669 · PC2 1.509PC1 1.183 · PC2 2.72PC1 -1.991 · PC2 -0.9776PC1 -2.097 · PC2 -0.7808PC1 -3.126 · PC2 -0.366PC1 -2.895 · PC2 -0.01584PC1 -2.31 · PC2 -0.5211PC1 -2.654 · PC2 -0.6678PC1 -2.935 · PC2 -0.3063PC1 -2.601 · PC2 -0.4748PC1 -3.045 · PC2 -0.2846PC1 -3.07 · PC2 -0.3116PC1 2.027 · PC2 0.4214PC1 1.017 · PC2 -0.06012PC1 0.4321 · PC2 -0.8948PC1 -0.2504 · PC2 -0.4599PC1 0.595 · PC2 -0.1906PC1 1.895 · PC2 -0.7231PC1 0.6009 · PC2 -0.7504PC1 1.404 · PC2 -1.612PC1 -0.891 · PC2 0.1522PC1 -2.537 · PC2 -0.2373PC1 -2.541 · PC2 0.944PC1 -2.022 · PC2 0.7632PC1 0.352 · PC2 -0.2617PC1 0.5071 · PC2 -0.552PC1 -0.2212 · PC2 -0.5222PC1 0.8723 · PC2 -0.1676PC1 2.196 · PC2 0.6611PC1 2.394 · PC2 0.3429PC1 -1.617 · PC2 0.6775PC1 0.8487 · PC2 -0.2758PC1 -2.53 · PC2 0.8651PC1 0.2732 · PC2 -0.5121PC1 0.001678 · PC2 0.0377PC1 -0.325 · PC2 -0.7376PC1 0.5992 · PC2 0.4074PC1 -1.436 · PC2 -0.3774PC1 -1.366 · PC2 -0.04329PC1 0.4099 · PC2 0.04677PC1 1.738 · PC2 -0.1655PC1 0.7728 · PC2 -0.326PC1 0.5356 · PC2 -0.1627PC1 1.664 · PC2 -0.5393PC1 1.335 · PC2 0.2573PC1 1.407 · PC2 -0.08949PC1 0.7999 · PC2 0.1944PC1 0.08544 · PC2 -0.3326PC1 -0.5013 · PC2 -0.1319PC1 1.209 · PC2 0.6224PC1 1.151 · PC2 -1.193PC1 1.65 · PC2 -1.077PC1 -0.03038 · PC2 -0.5712PC1 -0.129 · PC2 -0.8432PC1 0.4405 · PC2 -1.153PC1 0.1176 · PC2 -0.5087PC1 2.038 · PC2 -0.2672PC1 -1.083 · PC2 0.2044PC1 0.2003 · PC2 1.529PC1 -0.3501 · PC2 -1.725PC1 -0.1101 · PC2 -1.553PC1 1.738 · PC2 -1.412PC1 1.574 · PC2 -1.516PC1 2.214 · PC2 0.5974PC1 0.2477 · PC2 -0.5313PC1 0.2718 · PC2 -0.5034PC1 -1.312 · PC2 0.4254PC1 -0.04389 · PC2 0.1476PC1 -0.6095 · PC2 0.3986PC1 0.9243 · PC2 -0.3468PC1 -0.9552 · PC2 0.7072PC1 -2.284 · PC2 1.323PC1 2.912 · PC2 0.4241PC1 -0.4013 · PC2 -1.962PC1 -0.6611 · PC2 -2.024PC1 -2.631 · PC2 -0.218PC1 -3.241 · PC2 0.04048PC1 1.481 · PC2 0.2336PC1 -0.1463 · PC2 0.3132PC1 0.3457 · PC2 0.9078PC1 -0.0941 · PC2 0.4514PC1 -0.7425 · PC2 0.8544PC1 1.868 · PC2 -1.009PC1 -1.198 · PC2 -1.902PC1 -0.6332 · PC2 -1.992PC1 1.88 · PC2 0.0135PC1 -0.9895 · PC2 1.098PC1 0.6348 · PC2 -0.9933PC1 2.825 · PC2 0.6474PC1 2.958 · PC2 0.3031PC1 1.356 · PC2 -1.09PC1 1.552 · PC2 -1.486PC1 -0.278 · PC2 -0.6691PC1 -0.01698 · PC2 -0.6531PC1 0.2338 · PC2 0.8099PC1 0.9324 · PC2 -0.6948PC1 -0.2187 · PC2 0.9579PC1 -0.3049 · PC2 -0.8055PC1 -0.5044 · PC2 0.7688PC1 0.4271 · PC2 -0.7362PC1 -0.11 · PC2 -0.7108PC1 0.6512 · PC2 0.4913PC1 -0.2169 · PC2 0.765PC1 -0.7624 · PC2 0.09842PC1 1.147 · PC2 0.04226PC1 -1.524 · PC2 -1.548PC1 -1.671 · PC2 -1.434PC1 0.7916 · PC2 1.121PC1 0.1456 · PC2 1.223PC1 0.06032 · PC2 -1.513PC1 -0.5385 · PC2 -1.261PC1 0.3863 · PC2 1.35PC1 0.0319 · PC2 0.2217PC1 -0.0521 · PC2 0.04398PC1 0.2128 · PC2 0.1162PC1 -0.09567 · PC2 -0.2719PC1 -0.2836 · PC2 -0.3126PC1 -0.1226 · PC2 0.1577PC1 0.7131 · PC2 0.09456PC1 -0.3358 · PC2 0.02764PC1 0.543 · PC2 0.7276PC1 0.2578 · PC2 0.5174PC1 0.2421 · PC2 -0.2146PC1 0.5396 · PC2 0.2588PC1 -0.4752 · PC2 0.6942PC1 0.4506 · PC2 0.06649PC1 0.01542 · PC2 -0.336PC1 -0.4001 · PC2 0.4017PC1 0.472 · PC2 0.05501PC1 1.565 · PC2 -0.7134PC1 0.7765 · PC2 -0.3662PC1 0.1422 · PC2 1.384PC1 0.003228 · PC2 1.291PC1 1 · PC2 0.1171PC1 0.9734 · PC2 0.1894PC1 -0.4811 · PC2 0.5234PC1 -0.04631 · PC2 0.02423PC1 0.4086 · PC2 -0.3901PC1 0.2415 · PC2 -1.286PC1 0.1824 · PC2 0.4236PC1 1.442 · PC2 -0.09742PC1 1.193 · PC2 -0.4365PC1 0.9404 · PC2 -0.3327PC1 -0.5156 · PC2 0.1241PC1 0.1455 · PC2 0.561PC1 0.9144 · PC2 1.043PC1 -0.5817 · PC2 0.04028PC1 0.09919 · PC2 0.7257PC1 1.374 · PC2 1.283PC1 0.01704 · PC2 0.7007PC1 -3.207 · PC2 -0.2534PC1 -0.28 · PC2 -0.9198PC1 -0.0389 · PC2 -1.018PC1 0.1183 · PC2 1.062PC1 -0.0425 · PC2 0.6031PC1 -0.3475 · PC2 0.3429PC1 -0.01092 · PC2 0.5635PC1 -1.283 · PC2 -0.1021PC1 -3.739 · PC2 0.7142PC1 1.523 · PC2 1.051PC1 -5.55 · PC2 0.1283PC1 0.5572 · PC2 -1.248PC1 -0.002859 · PC2 0.4416PC1 0.1623 · PC2 0.3865PC1 -0.6276 · PC2 0.01985PC1 2.356 · PC2 -0.3468PC1 -0.621 · PC2 0.7706PC1 1.23 · PC2 0.7946PC1 2.046 · PC2 1.294PC1 0.4196 · PC2 -0.1154PC1 1.658 · PC2 0.9568PC1 -0.9318 · PC2 -0.113PC1 0.9574 · PC2 -0.07303PC1 1.278 · PC2 0.1076PC1 -2.669 · PC2 1.208PC1 0.6227 · PC2 -0.1123PC1 1.559 · PC2 1.123PC1 0.3214 · PC2 0.3988PC1 -0.122 · PC2 0.3002PC1 0.7704 · PC2 -0.2557PC1 1.512 · PC2 0.3107PC1 1.35 · PC2 0.3051PC1 1.405 · PC2 0.2324PC1 1.444 · PC2 1.414PC1 -4.989 · PC2 0.2539PC1 -3.565 · PC2 -0.4847PC1 2.551 · PC2 0.4572PC1 -4.301 · PC2 -0.2003PC1 -1.638 · PC2 -0.8609PC1 -3.729 · PC2 -1.135PC1 0.9673 · PC2 0.7324PC1 -5.064 · PC2 -0.354PC1 -2.683 · PC2 0.4967PC1 0.2816 · PC2 0.6949PC1 0.4681 · PC2 0.6759PC1 1.296 · PC2 1.432PC1 -0.2298 · PC2 -0.2447PC1 -0.2813 · PC2 0.05713PC1 1.329 · PC2 1.383PC1 -0.49 · PC2 -0.442PC1 0.3107 · PC2 0.8819PC1 0.8481 · PC2 0.2855PC1 1.269 · PC2 0.1219PC1 -0.2171 · PC2 0.4242PC1 -0.03125 · PC2 0.7033PC1 0.9787 · PC2 1.087PC1 -1.389 · PC2 -1.053PC1 -5.09 · PC2 -0.07721PC1 -0.943 · PC2 -1.18PC1 -4.611 · PC2 -0.2591PC1 0.7831 · PC2 0.969PC1 -1.92 · PC2 -1.153PC1 -3.416 · PC2 -1.401PC1 -4.441 · PC2 -0.7991PC1 -3.107 · PC2 0.6323PC1 0.7542 · PC2 -1.277PC1 0.3407 · PC2 -0.4461PC1 1.499 · PC2 -0.2614PC1 -0.6169 · PC2 -1.589PC1 1.588 · PC2 -1.273PC1 0.5432 · PC2 -0.9493PC1 1.044 · PC2 -0.8418PC1 0.1577 · PC2 -1.272PC1 5.042 · PC2 -2.558PC1 3.64 · PC2 -1.693PC1 3.706 · PC2 -2.238PC1 4.138 · PC2 -1.908PC1 1.637 · PC2 -0.499PC1 -0.6269 · PC2 0.6934PC1 -0.0699 · PC2 0.8012PC1 4.245 · PC2 -2.361PC1 -0.3755 · PC2 -0.9184PC1 -0.04688 · PC2 0.5484PC1 -0.5879 · PC2 0.5175PC1 -0.5902 · PC2 -0.8955PC1 1.787 · PC2 0.6615PC1 -0.0927 · PC2 -1.163PC1 0.05126 · PC2 0.6541PC1 -0.3725 · PC2 -1.436PC1 -0.4492 · PC2 -1.285PC1 -0.1438 · PC2 0.5801PC1 3.259 · PC2 -0.7111PC1 2.943 · PC2 -1.313PC1 3.163 · PC2 -1.703PC1 4.646 · PC2 -2.415PC1 -0.3735 · PC2 0.2485PC1 3.398 · PC2 -1.471PC1 -0.753 · PC2 0.6697PC1 3.354 · PC2 0.2838PC1 2.12 · PC2 -0.6686PC1 2.221 · PC2 -1.537PC1 0.2501 · PC2 -0.8383PC1 -1.081 · PC2 -1.008PC1 -1.092 · PC2 0.6431PC1 -0.3923 · PC2 -0.8286PC1 -1.379 · PC2 0.6021PC1 1.853 · PC2 -0.7757PC1 -1.468 · PC2 1.027PC1 3.571 · PC2 -0.5596PC1 -1.032 · PC2 -1.206PC1 2.102 · PC2 -0.7751PC1 1.742 · PC2 -1.687PC1 3.531 · PC2 -1.961PC1 2.183 · PC2 -1.466PC1 0.9227 · PC2 -1.19PC1 0.1454 · PC2 -0.3766PC1 0.9114 · PC2 -0.7256PC1 1.004 · PC2 -0.3586PC1 -0.09161 · PC2 -1.44PC1 0.2389 · PC2 -1.372PC1 -0.8236 · PC2 -1.266PC1 -0.7163 · PC2 -1.204PC1 -0.8351 · PC2 -0.6359PC1 -0.3094 · PC2 -0.9104PC1 -0.4281 · PC2 -1.263PC1 -5.069 · PC2 0.9517PC1 -1.596 · PC2 0.8837PC1 -2.28 · PC2 1.07PC1 -2.649 · PC2 0.2419PC1 -3.752 · PC2 0.4256PC1 -1.678 · PC2 0.5476PC1 -1.249 · PC2 -0.3806PC1 -3.201 · PC2 0.4573PC1 -2.719 · PC2 0.184PC1 -2.391 · PC2 1.218PC1 -1.538 · PC2 1.177PC1 -2.238 · PC2 1.581PC1 -1.965 · PC2 1.503PC1 -0.127 · PC2 2.249PC1 -2.749 · PC2 2.349PC1 -2.955 · PC2 1.212PC1 -2.07 · PC2 1.56PC1 -2.067 · PC2 1.893PC1 -1.347 · PC2 1.89PC1 1.003 · PC2 -0.0169PC1 -0.4076 · PC2 0.3281PC1 0.9947 · PC2 -0.01958PC1 -2.009 · PC2 -1.873PC1 -0.9138 · PC2 0.1276PC1 -0.9427 · PC2 0.2877PC1 0.171 · PC2 -0.1375PC1 -0.2388 · PC2 0.3461PC1 -0.7361 · PC2 -0.03723PC1 -0.4898 · PC2 -0.6789PC1 -0.7543 · PC2 -0.347PC1 -0.441 · PC2 -0.4138PC1 -0.1976 · PC2 -0.5302PC1 -0.4327 · PC2 -0.1211PC1 -1.146 · PC2 -1.178PC1 -1.096 · PC2 -1.21PC1 -1.644 · PC2 -1.222PC1 -2.29 · PC2 -0.4197PC1 -1.571 · PC2 -0.9607PC1 2.193 · PC2 0.9962PC1 1.616 · PC2 1.274PC1 1.659 · PC2 0.6802PC1 2.184 · PC2 0.6807PC1 0.4141 · PC2 0.289PC1 0.4573 · PC2 0.5594PC1 0.1578 · PC2 0.6974PC1 0.1701 · PC2 0.9127PC1 0.4878 · PC2 0.4255PC1 0.652 · PC2 -0.6441PC1 1.296 · PC2 -1.198PC1 0.5732 · PC2 0.565PC1 -0.778 · PC2 0.5177PC1 0.05693 · PC2 0.7178PC1 0.431 · PC2 1.029PC1 -0.2084 · PC2 0.4627PC1 0.03012 · PC2 0.2394PC1 -0.5901 · PC2 0.7976PC1 -0.09249 · PC2 0.4857PC1 0.7611 · PC2 0.6515PC1 -1.708 · PC2 0.4477PC1 -1.574 · PC2 1.22PC1 0.8279 · PC2 -0.1827PC1 -0.2808 · PC2 -0.5696PC1 -0.3377 · PC2 -0.2089PC1 -0.9224 · PC2 -0.8004PC1 0.2365 · PC2 -0.6608PC1 -0.04606 · PC2 -0.2658PC1 0.875 · PC2 -0.03494PC1 0.3272 · PC2 -0.4781PC1 0.7491 · PC2 -0.236PC1 -0.2323 · PC2 -0.3344PC1 0.1727 · PC2 -0.7705PC1 -0.03709 · PC2 -0.1199PC1 0.8013 · PC2 -0.3924PC1 0.5269 · PC2 -0.8378PC1 -0.9924 · PC2 -0.4901PC1 0.06336 · PC2 -0.7118PC1 -0.3182 · PC2 -0.6754PC1 -0.3778 · PC2 -0.6407PC1 -0.6768 · PC2 -0.2425PC1 -0.7963 · PC2 0.5934PC1 -0.6554 · PC2 0.03854PC1 -0.5 · PC2 0.5488PC1 -0.6921 · PC2 0.3907PC1 -1.073 · PC2 -2.137PC1 -0.3637 · PC2 -1.862PC1 -0.7483 · PC2 -2.136PC1 -0.5689 · PC2 -0.4862PC1 -0.7809 · PC2 -0.3558PC1 -0.9091 · PC2 -0.5448PC1 -0.9562 · PC2 -0.303PC1 0.5783 · PC2 -0.2706PC1 -0.4134 · PC2 -0.527PC1 0.2876 · PC2 -0.5343PC1 0.4677 · PC2 -0.05597PC1 -0.3044 · PC2 -0.2681PC1 0.4364 · PC2 0.153PC1 0.8541 · PC2 -0.04677PC1 0.056 · PC2 0.2499PC1 0.4426 · PC2 0.3461PC1 0.1908 · PC2 -0.02705PC1 -0.6127 · PC2 0.2968PC1 -0.5272 · PC2 0.2604PC1 -1.129 · PC2 -2.079PC1 -0.7244 · PC2 -2.347PC1 -0.595 · PC2 -2.122PC1 -0.5844 · PC2 -2.039PC1 -0.7018 · PC2 -2.175PC1 -0.4308 · PC2 -0.8474PC1 -0.5813 · PC2 -0.07818PC1 -0.05493 · PC2 -0.2243PC1 -0.5552 · PC2 0.1265PC1 -0.1037 · PC2 -0.5365PC1 0.1249 · PC2 -0.2722PC1 0.2183 · PC2 -0.3456PC1 0.3477 · PC2 -0.5884PC1 0.355 · PC2 -0.4871PC1 0.6044 · PC2 0.2929PC1 0.2056 · PC2 0.4105PC1 0.7121 · PC2 0.4791PC1 0.8995 · PC2 0.3675PC1 0.3632 · PC2 0.4154PC1 -0.6642 · PC2 0.6307PC1 -0.6661 · PC2 0.05869PC1 -0.5733 · PC2 -1.988PC1 -0.7612 · PC2 -1.99PC1 0.03044 · PC2 -1.898PC1 0.1124 · PC2 -0.1138PC1 1.018 · PC2 -0.08242PC1 0.816 · PC2 -0.02543PC1 -0.09307 · PC2 -0.1988PC1 0.2467 · PC2 -0.1691PC1 1.026 · PC2 -0.04461PC1 0.05353 · PC2 -0.4057PC1 0.6353 · PC2 -0.1773PC1 0.1817 · PC2 -0.4213PC1 0.718 · PC2 -0.1003PC1 0.6212 · PC2 0.1934PC1 0.7581 · PC2 -0.003377PC1 0.2265 · PC2 0.1918PC1 -0.5187 · PC2 0.5995PC1 0.5071 · PC2 0.6139PC1 0.1984 · PC2 0.7321PC1 -0.1162 · PC2 0.1487PC1 0.2798 · PC2 0.5626PC1 0.1372 · PC2 -2.261PC1 0.5581 · PC2 -2.04PC1 0.1325 · PC2 -2.021PC1 -0.1255 · PC2 -2.153PC1 0.3379 · PC2 -0.01805PC1 -0.2166 · PC2 -0.2881PC1 -0.1074 · PC2 -0.01254PC1 0.1314 · PC2 -0.1735PC1 0.5282 · PC2 -0.09027PC1 0.2733 · PC2 0.1892PC1 0.6436 · PC2 0.2441PC1 0.7903 · PC2 0.002269PC1 0.2334 · PC2 0.2856PC1 0.4256 · PC2 0.04586PC1 -0.201 · PC2 -0.496PC1 0.002832 · PC2 -0.6473PC1 -0.4084 · PC2 -0.3426PC1 -0.5978 · PC2 0.4204PC1 -0.4297 · PC2 0.8839PC1 -0.9613 · PC2 0.9431PC1 -0.3761 · PC2 0.9456PC1 0.1598 · PC2 -2.008PC1 0.3833 · PC2 -1.791PC1 0.1964 · PC2 -1.963PC1 0.0781 · PC2 -1.57PC1 0.1507 · PC2 -1.923PC1 0.8603 · PC2 -0.2088PC1 0.541 · PC2 -0.2954PC1 0.4579 · PC2 -0.09398PC1 0.4693 · PC2 -0.1835PC1 0.4289 · PC2 -0.3418PC1 0.3881 · PC2 0.05853PC1 0.618 · PC2 -0.09719PC1 0.05283 · PC2 -0.09362PC1 -0.1869 · PC2 0.5495PC1 -0.655 · PC2 0.9001PC1 -0.06892 · PC2 -2.174PC1 0.4392 · PC2 -1.804PC1 0.01866 · PC2 -1.782PC1 0.1674 · PC2 -2.093PC1 0.6853 · PC2 -0.4936PC1 0.575 · PC2 -0.1379PC1 1.492 · PC2 -0.1921PC1 0.8447 · PC2 -0.3731PC1 0.2848 · PC2 -0.7729PC1 0.2151 · PC2 -1.118PC1 -1.665 · PC2 -0.6112PC1 -2.042 · PC2 -0.9049PC1 -1.5 · PC2 -0.7308PC1 -1.143 · PC2 -0.5604PC1 -1.567 · PC2 -1.152PC1 -1.866 · PC2 -0.8579PC1 -0.5878 · PC2 -1.23PC1 -1.169 · PC2 -1.095PC1 -2.262 · PC2 -0.963PC1 -1.296 · PC2 -0.6821PC1 -1.709 · PC2 -0.7239PC1 -1.87 · PC2 -0.3508PC1 -2.878 · PC2 -0.4302PC1 -1.497 · PC2 -1.187PC1 -1.373 · PC2 -1.379PC1 -1.536 · PC2 -1.15PC1 -0.9349 · PC2 -1.219PC1 -1.795 · PC2 -1.172PC1 -1.608 · PC2 -1.267PC1 -0.9897 · PC2 -1.465PC1 -1.832 · PC2 -1.586PC1 (66.5%)PC2 (26.2%)800 scores
View plotted PCA coordinates

Point numbers identify rows in this displayed coordinate list, not original observation or sample IDs. Non-integer coordinates use up to five significant digits. Original IDs, component loadings, preprocessing details and the observation selection method are not supplied with this plot.

Plotted observation positions (not original sample IDs)
PointPC1 scorePC2 score
1-0.24839-0.050398
20.4684-0.15412
30.203610.14255
40.716560.26743
50.377880.23766
60.98567-0.052586
70.94608-0.049842
80.362180.30207
90.356550.019406
101.18030.46286
111.0052-0.029438
120.528750.36772
131.23430.16296
14-0.52452-0.26627
151.0994-0.10327
160.50950.18774
170.280410.31992
180.131660.91242
190.148510.34533
200.0963180.23469
210.099870.30977
220.30370.82688
230.557650.7485
240.0900530.57938
25-0.133560.4106
26-0.56645-0.086663
27-0.41886-0.17428
28-0.53348-0.29192
29-0.43007-0.052384
30-0.30139-0.11337
31-0.36898-0.18258
320.370380.39034
330.486130.345
341.36930.65665
350.795650.023235
361.11660.30175
370.178190.18389
380.491730.23921
390.658040.040241
400.697390.095887
410.79156-0.03833
420.187940.23223
43-0.19592-0.26112
44-0.169120.42732
45-0.28045-0.00015228
46-0.49125-0.13452
470.730890.33437
480.548610.028753
490.29495-0.23913
500.849020.022659
510.582660.40233
520.38453-0.10384
53-0.26696-0.043062
54-0.039006-0.1443
550.847570.52693
560.851330.46604
570.361790.91596
580.556140.72742
590.588110.54136
600.756840.2879
611.38740.20758
621.11830.67688
631.19150.78918
64-0.52056-0.51448
65-0.50587-0.39244
660.547090.11251
670.551030.17364
68-0.06509-0.32908
690.714-0.25846
700.23830.036965
71-0.0447780.48215
720.0445410.90256
73-0.594320.028233
740.21736-0.028081
75-0.38193-0.51085
760.256780.096894
770.42326-0.12589
78-0.73531-0.15437
79-0.49974-0.26717
80-0.70322-0.48157
81-0.10776-0.3002
82-0.45246-0.23226
83-0.925490.45901
84-0.736480.4583
85-1.01370.12903
86-0.910160.071889
87-0.936540.25513
88-0.594620.42237
890.032974-0.037719
900.15132-0.6099
910.47954-0.382
920.078944-0.1125
930.352930.44749
940.815410.49104
951.27941.1078
960.519060.6023
970.644560.98895
980.518230.23949
991.20820.071563
1000.23691-0.34856
1010.17290.013595
1020.32584-0.30256
1030.49954-0.038478
104-0.315350.24305
105-0.281130.20812
1061.18730.62368
1071.3420.087006
1080.885820.8104
1090.986520.67847
1101.13140.86052
111-0.064337-0.14065
1120.902340.39038
113-0.50346-0.52813
1140.579180.35639
1151.08520.73231
1160.771560.53526
1171.17830.38413
1181.74710.12985
119-0.20531-0.021617
120-0.059932-0.13232
121-0.504760.0045068
122-0.0346540.061093
1230.516640.48513
1241.19590.62673
1251.1771-0.39153
1260.69461-0.47632
1270.25278-0.29041
1280.57711-0.21087
1291.42181.1083
1301.02311.068
1310.137290.27715
132-0.022302-0.10237
1330.33275-0.13062
1340.76467-0.073756
1350.445480.20657
1360.94681-0.062378
1371.35950.2663
1380.91953-0.36833
1391.164-0.06989
1400.291370.056439
1410.52318-0.12016
142-0.28873-0.45595
1430.835330.63428
144-0.22536-0.10138
145-0.24043-0.28074
146-0.2129-0.098415
147-0.19056-0.22828
1480.637381.5022
1491.630.2606
1500.994380.28354
1510.50506-0.12716
152-0.67129-0.32185
1530.17101-0.32711
1540.887910.40581
1550.795470.3175
1561.75690.8915
157-0.67342-0.13189
158-0.38048-0.23714
159-0.25322-0.50524
1600.927020.49327
1611.4920.25403
1620.84831.1508
1630.79870.52967
164-0.61857-0.46793
165-0.35633-0.5602
1660.703940.51674
1670.366740.36998
1681.7250.14363
1691.29630.69142
1701.1280.74868
171-0.25598-0.17214
172-0.46684-0.44194
1731.04250.3
174-0.49565-0.26557
175-0.53044-0.46764
176-0.044583-0.18489
177-0.28215-0.58699
178-4.98270.62939
179-3.9541-0.012582
180-3.99861.1001
181-0.284950.44631
1820.74181.3419
183-1.10630.96959
184-1.7276-0.21582
185-1.096-0.78519
186-3.50150.069198
1870.496831.6527
1880.61831.5753
1890.875521.1278
1900.658672.0922
1910.294470.37662
1920.63791-0.10332
1930.823710.82942
194-1.02080.75478
1950.5151.3782
1961.07850.66935
197-3.58890.52617
198-4.57560.42856
199-0.26940.16185
2001.1102-0.40126
2010.91485-0.59644
2021.46891.0043
2031.6080.21024
2041.47231.0477
2050.979610.5225
206-0.251350.21279
2070.27359-0.55831
2080.269740.60463
2090.404840.072682
2101.20670.30925
211-2.29280.51501
212-3.25330.67227
213-2.7495-0.41413
214-2.2689-0.55793
215-0.395960.25609
2160.762940.83995
2171.16121.1905
218-0.963640.19371
2190.656050.35486
2201.68361.4464
2210.76192-0.19105
2220.55527-0.22876
2230.049375-0.0066021
224-0.288760.71756
225-0.563040.92519
2260.0606291.3165
227-0.197660.082591
2280.692350.57901
229-0.47080.93784
230-0.456790.50104
231-0.21109-0.28856
232-0.78944-0.22148
233-0.0266750.29484
234-0.74411-0.41642
235-0.225740.26446
236-0.109080.26523
2371.10060.43826
2381.05950.0038274
2391.27370.94472
240-1.0890.066215
2410.619730.98424
242-0.58621-0.040059
243-0.85381.4887
244-0.406240.49015
2451.31660.54975
2460.652431.3451
2470.889441.3829
2480.965141.6056
249-0.118080.28848
250-0.503370.49607
251-0.845380.42371
252-0.00029892-0.17834
253-0.27180.17593
2540.205541.0626
2550.221091.1154
256-0.0555621.0285
2570.262031.23
258-0.00560960.74449
2590.705571.0218
2601.30440.93344
2610.30071.5051
2620.524160.8221
2630.593760.076572
2640.368751.7319
2650.80869-0.26232
2660.924231.3673
2671.10530.023959
2681.53590.46268
2691.30710.93988
2701.98491.227
2710.28531.3574
2721.23580.69231
2731.64011.4566
2740.0709911.4299
2750.141221.4437
2760.526121.2749
2770.159851.1304
2780.77251.1755
2790.953541.48
2800.428981.3665
2810.846071.4734
282-0.568390.78583
2831.13770.89828
2840.512090.29177
2850.57894-0.41978
2860.409680.10196
287-3.11520.42493
288-2.62430.5212
2890.942250.22086
2901.7398-0.80074
291-0.73588-0.024912
292-2.60680.36696
293-2.21890.40404
294-0.355891.0523
295-3.7676-0.3139
296-0.184020.40858
2970.0787550.30002
298-0.65453-0.028681
2991.1874-2.1458
300-0.67532-1.2351
3010.61142-1.3689
302-5.22730.61471
3030.0251440.83903
3040.0495420.70938
3051.64750.79293
3061.75230.27813
3070.743170.59493
308-1.1922-0.030941
3090.838632.2366
310-0.441780.82945
3110.492761.5196
3120.187611.9971
313-0.0870821.9027
3140.297181.7488
3150.36691.5091
3161.18312.7201
317-1.9905-0.97764
318-2.097-0.78084
319-3.126-0.36605
320-2.895-0.015842
321-2.3099-0.52112
322-2.6541-0.66783
323-2.9355-0.30628
324-2.6005-0.47476
325-3.0454-0.28459
326-3.07-0.31161
3272.02690.42141
3281.0168-0.060119
3290.43212-0.89479
330-0.25036-0.45991
3310.59496-0.19063
3321.8948-0.72305
3330.60089-0.75036
3341.4039-1.6116
335-0.891040.15216
336-2.5366-0.23727
337-2.54130.94402
338-2.0220.76316
3390.352-0.26173
3400.50707-0.55196
341-0.22118-0.52221
3420.87226-0.16757
3432.19580.66113
3442.39450.34287
345-1.6170.67751
3460.84872-0.27584
347-2.53030.8651
3480.27318-0.51207
3490.00167810.037698
350-0.32499-0.7376
3510.599190.40741
352-1.4356-0.37742
353-1.366-0.043293
3540.409860.046772
3551.738-0.16553
3560.77284-0.32598
3570.53564-0.16266
3581.6643-0.53928
3591.33450.25731
3601.407-0.089493
3610.79990.19443
3620.085439-0.3326
363-0.50129-0.13195
3641.20890.6224
3651.1508-1.1928
3661.6496-1.0768
367-0.030379-0.57118
368-0.12902-0.84322
3690.44049-1.1532
3700.11763-0.50875
3712.0379-0.26725
372-1.08340.20439
3730.200341.5292
374-0.35012-1.7248
375-0.11011-1.553
3761.7378-1.4122
3771.5742-1.516
3782.2140.59741
3790.24769-0.53134
3800.27183-0.50344
381-1.31150.42544
382-0.0438940.14757
383-0.609510.39855
3840.92429-0.34677
385-0.955240.70716
386-2.28381.3231
3872.9120.42409
388-0.40134-1.9618
389-0.66114-2.0241
390-2.631-0.21804
391-3.24120.040485
3921.48140.2336
393-0.146290.3132
3940.345710.9078
395-0.0941040.45139
396-0.742480.85443
3971.8682-1.0093
398-1.1975-1.9023
399-0.63323-1.9918
4001.880.013503
401-0.98951.0984
4020.6348-0.99331
4032.82530.64741
4042.95820.30306
4051.3559-1.0905
4061.552-1.4863
407-0.27805-0.66907
408-0.016981-0.65308
4090.233820.80989
4100.93239-0.69483
411-0.218730.95787
412-0.30494-0.80547
413-0.504390.76877
4140.4271-0.7362
415-0.10997-0.7108
4160.651220.4913
417-0.216860.76501
418-0.762380.098422
4191.14730.042265
420-1.524-1.5481
421-1.6706-1.4342
4220.791651.1211
4230.145561.2226
4240.060317-1.5129
425-0.53853-1.2614
4260.386341.3497
4270.0319020.22166
428-0.0520970.043982
4290.212760.11617
430-0.095667-0.27192
431-0.28356-0.3126
432-0.122580.15773
4330.713070.094559
434-0.335820.02764
4350.543030.72759
4360.257830.51742
4370.2421-0.21462
4380.539650.25878
439-0.475150.69419
4400.450610.066494
4410.015417-0.33599
442-0.40010.40168
4430.472020.055009
4441.5653-0.71343
4450.77651-0.36618
4460.14221.3837
4470.00322811.2906
4481.00010.11713
4490.973440.18935
450-0.481110.52342
451-0.0463090.024227
4520.40863-0.39008
4530.24147-1.2856
4540.182450.42357
4551.4424-0.09742
4561.1931-0.4365
4570.94038-0.33273
458-0.515640.12414
4590.145530.56104
4600.91441.0433
461-0.581740.040285
4620.0991890.72572
4631.37431.2829
4640.0170360.7007
465-3.2072-0.25341
466-0.28004-0.91977
467-0.038895-1.0181
4680.11831.0615
469-0.0424980.60307
470-0.347450.34285
471-0.010920.56347
472-1.2834-0.10212
473-3.73910.71424
4741.52291.0509
475-5.54960.12827
4760.55724-1.2475
477-0.00285880.44164
4780.16230.38649
479-0.627620.019852
4802.3558-0.34684
481-0.621050.77062
4821.23010.79465
4832.0461.2936
4840.41959-0.11543
4851.65770.95677
486-0.93179-0.11304
4870.95739-0.073032
4881.2780.10756
489-2.66881.2085
4900.62267-0.11233
4911.55861.1229
4920.321380.3988
493-0.1220.30022
4940.77039-0.25566
4951.51190.31067
4961.34960.30507
4971.40530.23244
4981.44371.4139
499-4.98870.25393
500-3.5645-0.48474
5012.55110.45724
502-4.3011-0.20034
503-1.6383-0.86087
504-3.7291-1.1353
5050.967270.73243
506-5.0644-0.35405
507-2.68330.49666
5080.281580.69492
5090.468110.67589
5101.2961.4318
511-0.22985-0.24474
512-0.281270.057131
5131.32881.3829
514-0.48996-0.44203
5150.310750.88188
5160.84810.28549
5171.26880.12195
518-0.217050.4242
519-0.0312450.70328
5200.978691.0872
521-1.3886-1.0526
522-5.0902-0.077211
523-0.94297-1.18
524-4.6112-0.25915
5250.78310.96899
526-1.9204-1.1534
527-3.4157-1.4008
528-4.4411-0.79906
529-3.10690.6323
5300.75421-1.2774
5310.34071-0.44605
5321.4988-0.26136
533-0.61686-1.5888
5341.5877-1.2729
5350.54321-0.94931
5361.0437-0.84183
5370.1577-1.2716
5385.0419-2.5582
5393.6397-1.693
5403.7061-2.2379
5414.1383-1.908
5421.6368-0.49896
543-0.62690.69339
544-0.0699030.80124
5454.2455-2.3615
546-0.37549-0.91844
547-0.0468750.54839
548-0.587890.51749
549-0.59022-0.89547
5501.7870.66147
551-0.092695-1.1629
5520.051260.65407
553-0.37247-1.4356
554-0.44924-1.2851
555-0.143840.58014
5563.2593-0.71105
5572.9425-1.3133
5583.1632-1.7034
5594.6464-2.4147
560-0.373490.24845
5613.398-1.4714
562-0.752960.66972
5633.35370.28382
5642.1199-0.66856
5652.2208-1.5369
5660.25011-0.83828
567-1.0809-1.0082
568-1.09240.64312
569-0.39225-0.82864
570-1.37870.60205
5711.8534-0.77567
572-1.46851.027
5733.5712-0.55964
574-1.0324-1.2059
5752.1018-0.7751
5761.742-1.6874
5773.5312-1.9612
5782.1826-1.466
5790.92274-1.1898
5800.14545-0.37662
5810.91136-0.72561
5821.0037-0.3586
583-0.091608-1.4399
5840.23892-1.3715
585-0.82356-1.2659
586-0.71626-1.2045
587-0.83515-0.63591
588-0.30942-0.91037
589-0.42815-1.2629
590-5.06920.95172
591-1.59570.88372
592-2.28021.0699
593-2.64910.24187
594-3.75170.42558
595-1.67780.54764
596-1.2488-0.3806
597-3.20090.4573
598-2.71910.18399
599-2.39081.2184
600-1.53771.1773
601-2.23761.5809
602-1.96451.5031
603-0.127012.2489
604-2.74892.3495
605-2.95481.2122
606-2.06971.5602
607-2.06711.8929
608-1.34651.8905
6091.0029-0.016904
610-0.407650.32815
6110.99474-0.019582
612-2.0095-1.8726
613-0.913820.12756
614-0.942710.28772
6150.17103-0.13748
616-0.238820.34607
617-0.73613-0.037231
618-0.48984-0.67892
619-0.75432-0.34701
620-0.44102-0.41384
621-0.19757-0.53017
622-0.43275-0.12106
623-1.1458-1.1778
624-1.096-1.2103
625-1.6438-1.2223
626-2.29-0.41973
627-1.5706-0.96074
6282.19310.99621
6291.61561.2735
6301.65930.68019
6312.18360.6807
6320.414050.28901
6330.457310.55942
6340.15780.69742
6350.170150.91269
6360.487820.42546
6370.65199-0.64412
6381.2964-1.198
6390.573230.56501
640-0.778030.5177
6410.056930.71783
6420.431031.029
643-0.208450.46265
6440.0301190.23941
645-0.590150.79758
646-0.0924920.48574
6470.761120.65147
648-1.70770.44772
649-1.57421.22
6500.82791-0.18272
651-0.2808-0.56964
652-0.33767-0.20889
653-0.92241-0.8004
6540.23653-0.66081
655-0.046063-0.26577
6560.87504-0.034938
6570.32724-0.47806
6580.74914-0.23603
659-0.23229-0.33443
6600.17268-0.77053
661-0.037088-0.11993
6620.8013-0.39239
6630.52694-0.83782
664-0.99241-0.4901
6650.06336-0.7118
666-0.3182-0.67541
667-0.37783-0.6407
668-0.67683-0.24251
669-0.796280.5934
670-0.655390.038538
671-0.499960.54881
672-0.692090.39067
673-1.0726-2.137
674-0.36372-1.8624
675-0.74833-2.136
676-0.5689-0.48621
677-0.78086-0.35581
678-0.90908-0.54478
679-0.95624-0.30296
6800.57827-0.27062
681-0.41338-0.52701
6820.28758-0.53427
6830.46771-0.055972
684-0.30443-0.26809
6850.436430.15298
6860.85408-0.046772
6870.0560.24991
6880.442560.3461
6890.19078-0.027048
690-0.61270.29676
691-0.527190.26042
692-1.1295-2.0787
693-0.72441-2.347
694-0.59504-2.1224
695-0.58444-2.0388
696-0.70181-2.1755
697-0.43076-0.8474
698-0.58129-0.078175
699-0.05493-0.22429
700-0.555230.12649
701-0.10372-0.53645
7020.12494-0.27217
7030.2183-0.34556
7040.34768-0.58843
7050.35496-0.48714
7060.604360.29292
7070.20560.41051
7080.712130.47915
7090.899520.36748
7100.363190.41545
711-0.664220.63073
712-0.666050.05869
713-0.57329-1.9879
714-0.76116-1.9897
7150.03044-1.8981
7160.11237-0.11381
7171.0181-0.082423
7180.81597-0.02543
719-0.093072-0.19883
7200.24674-0.16913
7211.0263-0.044607
7220.053531-0.40569
7230.63528-0.17726
7240.18166-0.42125
7250.71798-0.10032
7260.621170.19341
7270.75807-0.003377
7280.22650.19176
729-0.518730.59951
7300.50710.61389
7310.198450.73206
732-0.116150.14866
7330.279830.56259
7340.1372-2.2608
7350.55807-2.0396
7360.13246-2.021
737-0.12549-2.1533
7380.33793-0.018053
739-0.21657-0.28812
740-0.1074-0.012539
7410.13145-0.17354
7420.52823-0.090273
7430.273320.18924
7440.643640.24406
7450.79030.0022695
7460.233350.28564
7470.425640.045861
748-0.20099-0.49604
7490.0028325-0.64726
750-0.40836-0.34259
751-0.597760.42038
752-0.429720.88393
753-0.96130.94312
754-0.376130.94558
7550.15982-2.0082
7560.38331-1.7913
7570.19638-1.9628
7580.078097-1.5703
7590.15071-1.9233
7600.86034-0.20875
7610.54104-0.29542
7620.4579-0.093981
7630.46929-0.18346
7640.4289-0.34177
7650.388150.058533
7660.61796-0.097191
7670.052833-0.093621
768-0.186920.54945
769-0.654980.90006
770-0.068921-2.1741
7710.43916-1.8039
7720.018662-1.7817
7730.16743-2.0928
7740.68531-0.49363
7750.57504-0.13785
7761.4918-0.19211
7770.84468-0.37313
7780.28478-0.77295
7790.21513-1.1183
780-1.6652-0.61119
781-2.0419-0.90489
782-1.4998-0.73081
783-1.1431-0.5604
784-1.5667-1.1523
785-1.8662-0.85789
786-0.58784-1.2304
787-1.1688-1.0952
788-2.262-0.963
789-1.2964-0.68207
790-1.7089-0.72389
791-1.8698-0.35082
792-2.8782-0.43023
793-1.4974-1.1867
794-1.3733-1.3791
795-1.5363-1.15
796-0.93493-1.219
797-1.7952-1.1725
798-1.6081-1.267
799-0.98968-1.4646
800-1.8317-1.5865

PCA explained variance — how many dimensions?

Each bar reports the share of spectral variance explained by a component. Concentration in the first components indicates correlated wavelengths. This is not variance explained in the prediction target. This projection may use a different observation sample from the score plot.

PCA explained variance0%25%50%75%100%PC1: 66.6% (cumulative 66.6%)1PC2: 26.1% (cumulative 92.7%)2PC3: 4.9% (cumulative 97.6%)3PC4: 0.8% (cumulative 98.4%)4PC5: 0.5% (cumulative 99.0%)5PC6: 0.4% (cumulative 99.4%)6PC7: 0.3% (cumulative 99.6%)7PC8: 0.1% (cumulative 99.7%)8PC9: 0.1% (cumulative 99.8%)9PC10: 0.0% (cumulative 99.8%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
View explained variance values
Variance per displayed principal component
ComponentSpectral variance
PC166.61%
PC226.08%
PC34.90%
PC40.82%
PC50.54%
PC60.43%
PC70.26%
PC80.10%
PC90.06%
PC100.03%
X-Y spectral correlation 20

Pearson r measures the linear association between each spectral channel (X) and a numeric target (Y), from −1 to +1. The table reports peak and average absolute correlation and the share of channels with |r| ≥ 0.5. These are in-dataset associations, not validation scores or proof of causation.

Spectral association with LMA

Read Pearson correlation (−1 to +1) along the spectral axis (nm); the solid curve shows |r| and the dashed curve shows signed r.

X_reflectance · LMA spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale

Spectral association with LDMC

Read Pearson correlation (−1 to +1) along the spectral axis (nm); the solid curve shows |r| and the dashed curve shows signed r.

X_reflectance · LDMC spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale

Spectral association with EWT

Read Pearson correlation (−1 to +1) along the spectral axis (nm); the solid curve shows |r| and the dashed curve shows signed r.

X_reflectance · EWT spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
LMA0.6671,7260.37842.9%
LDMC0.365320.1260.0%
EWT0.7361,4970.39851.4%
Cmass0.4135190.1340.0%
Nmass0.2841,7180.1360.0%
solubles_mass0.5054380.1051.5%
hemicellulose_mass0.5614370.1044.3%
cellulose_mass0.5634570.184.6%
lignin_mass0.4725150.1520.0%
chlA_mass0.3412,2930.1660.0%
chlB_mass0.3532,2960.160.0%
car_mass0.352,2910.1730.0%
Al_mass0.3395010.1630.0%
B208.9_mass0.157010.02640.0%
B249.8_mass0.1517020.02820.0%
Ca_mass0.2761,9480.1350.0%
Cu_mass0.4146430.1780.0%
Fe_mass0.3552,1360.1930.0%
K_mass0.1942,2680.1020.0%
Mg_mass0.1866260.08940.0%

trans_spec.csv

X_transmittance · NIR · Spectra Vista Corporation HR-1024i

Read the signal and variation summaries for this source. Axis unit: nm; signal representation: not recorded.

Spectral signal summary

The mean and median describe the typical signal at each channel; shaded bands show the 25th–75th and 5th–95th percentiles across observations. A wider band means greater variation, which can be biological or instrumental.

trans_spec.csv spectra-0.20.00.20.40.605001,0001,5002,0002,500q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm400nm — median 0.003046 (q25–q75 0.0007147–0.004395)414nm — median 0.004252 (q25–q75 0.002414–0.006823)429nm — median 0.007531 (q25–q75 0.004708–0.01103)443nm — median 0.00993 (q25–q75 0.006446–0.01423)458nm — median 0.01373 (q25–q75 0.009079–0.01924)472nm — median 0.01501 (q25–q75 0.01009–0.02091)486nm — median 0.01671 (q25–q75 0.01136–0.02317)501nm — median 0.02414 (q25–q75 0.01611–0.03275)515nm — median 0.04925 (q25–q75 0.03265–0.06522)529nm — median 0.0907 (q25–q75 0.06415–0.1142)544nm — median 0.1092 (q25–q75 0.07994–0.1358)558nm — median 0.1116 (q25–q75 0.08224–0.1384)573nm — median 0.09105 (q25–q75 0.06514–0.1147)587nm — median 0.07386 (q25–q75 0.05217–0.0954)601nm — median 0.06815 (q25–q75 0.04824–0.08858)616nm — median 0.05706 (q25–q75 0.0401–0.07541)630nm — median 0.05143 (q25–q75 0.03634–0.06849)645nm — median 0.0412 (q25–q75 0.02954–0.05473)659nm — median 0.03086 (q25–q75 0.02243–0.04153)673nm — median 0.02195 (q25–q75 0.01583–0.02898)688nm — median 0.03365 (q25–q75 0.02426–0.04429)702nm — median 0.1319 (q25–q75 0.1022–0.1603)717nm — median 0.2546 (q25–q75 0.2193–0.2829)731nm — median 0.3374 (q25–q75 0.3047–0.3603)745nm — median 0.3795 (q25–q75 0.3492–0.399)760nm — median 0.3952 (q25–q75 0.3656–0.4146)774nm — median 0.4005 (q25–q75 0.3715–0.4199)788nm — median 0.404 (q25–q75 0.3749–0.4229)803nm — median 0.4067 (q25–q75 0.378–0.4255)817nm — median 0.409 (q25–q75 0.3806–0.4277)832nm — median 0.4114 (q25–q75 0.3833–0.43)846nm — median 0.4138 (q25–q75 0.3859–0.4321)860nm — median 0.4162 (q25–q75 0.3884–0.4344)875nm — median 0.4185 (q25–q75 0.3907–0.4367)889nm — median 0.4204 (q25–q75 0.3929–0.4387)904nm — median 0.4224 (q25–q75 0.3954–0.4407)918nm — median 0.4244 (q25–q75 0.3973–0.4426)932nm — median 0.4258 (q25–q75 0.3989–0.4438)947nm — median 0.4263 (q25–q75 0.3993–0.4442)961nm — median 0.4253 (q25–q75 0.398–0.4434)976nm — median 0.4268 (q25–q75 0.3995–0.4448)990nm — median 0.429 (q25–q75 0.402–0.4474)1,004nm — median 0.4316 (q25–q75 0.4042–0.4498)1,019nm — median 0.4351 (q25–q75 0.408–0.4535)1,033nm — median 0.4382 (q25–q75 0.4116–0.4568)1,047nm — median 0.4409 (q25–q75 0.4144–0.4596)1,062nm — median 0.4431 (q25–q75 0.4175–0.4619)1,076nm — median 0.4449 (q25–q75 0.4194–0.4636)1,091nm — median 0.4465 (q25–q75 0.4212–0.465)1,105nm — median 0.4475 (q25–q75 0.4219–0.466)1,119nm — median 0.4483 (q25–q75 0.4223–0.467)1,134nm — median 0.4472 (q25–q75 0.4203–0.4659)1,148nm — median 0.4419 (q25–q75 0.4137–0.4608)1,163nm — median 0.4381 (q25–q75 0.4078–0.4572)1,177nm — median 0.4377 (q25–q75 0.4069–0.4571)1,191nm — median 0.438 (q25–q75 0.4068–0.4576)1,206nm — median 0.4396 (q25–q75 0.4081–0.4591)1,220nm — median 0.442 (q25–q75 0.4118–0.4615)1,235nm — median 0.445 (q25–q75 0.4154–0.4644)1,249nm — median 0.4473 (q25–q75 0.4174–0.4664)1,263nm — median 0.4485 (q25–q75 0.4191–0.4676)1,278nm — median 0.4495 (q25–q75 0.42–0.4685)1,292nm — median 0.449 (q25–q75 0.4192–0.4681)1,306nm — median 0.4468 (q25–q75 0.4168–0.4661)1,321nm — median 0.4416 (q25–q75 0.4094–0.4609)1,335nm — median 0.4336 (q25–q75 0.3986–0.453)1,350nm — median 0.4235 (q25–q75 0.3854–0.4437)1,364nm — median 0.4144 (q25–q75 0.3731–0.4351)1,378nm — median 0.3944 (q25–q75 0.3488–0.417)1,393nm — median 0.3409 (q25–q75 0.288–0.3689)1,407nm — median 0.2764 (q25–q75 0.2193–0.3079)1,422nm — median 0.2378 (q25–q75 0.1803–0.2715)1,436nm — median 0.2228 (q25–q75 0.1654–0.257)1,450nm — median 0.2203 (q25–q75 0.1639–0.255)1,465nm — median 0.227 (q25–q75 0.1695–0.2616)1,479nm — median 0.2402 (q25–q75 0.1823–0.2747)1,494nm — median 0.2599 (q25–q75 0.2009–0.2936)1,508nm — median 0.2794 (q25–q75 0.2199–0.3127)1,522nm — median 0.2971 (q25–q75 0.2383–0.3299)1,537nm — median 0.314 (q25–q75 0.2567–0.3466)1,551nm — median 0.3276 (q25–q75 0.2709–0.3591)1,565nm — median 0.3395 (q25–q75 0.284–0.3697)1,580nm — median 0.3503 (q25–q75 0.2953–0.3798)1,594nm — median 0.359 (q25–q75 0.3055–0.3877)1,609nm — median 0.3675 (q25–q75 0.3147–0.3954)1,623nm — median 0.3739 (q25–q75 0.3215–0.4016)1,637nm — median 0.3785 (q25–q75 0.3268–0.4062)1,652nm — median 0.3816 (q25–q75 0.3303–0.4093)1,666nm — median 0.3829 (q25–q75 0.3309–0.4107)1,681nm — median 0.3823 (q25–q75 0.329–0.41)1,695nm — median 0.3802 (q25–q75 0.326–0.4077)1,709nm — median 0.3763 (q25–q75 0.322–0.404)1,724nm — median 0.3714 (q25–q75 0.317–0.3999)1,738nm — median 0.3669 (q25–q75 0.3118–0.3957)1,753nm — median 0.3617 (q25–q75 0.3055–0.3903)1,767nm — median 0.3564 (q25–q75 0.3001–0.3857)1,781nm — median 0.3531 (q25–q75 0.2976–0.3824)1,796nm — median 0.3525 (q25–q75 0.2969–0.3822)1,810nm — median 0.3543 (q25–q75 0.2981–0.3836)1,824nm — median 0.3562 (q25–q75 0.3001–0.3855)1,839nm — median 0.3553 (q25–q75 0.2981–0.3847)1,853nm — median 0.3444 (q25–q75 0.2852–0.3741)1,868nm — median 0.3059 (q25–q75 0.248–0.3393)1,882nm — median 0.2389 (q25–q75 0.1804–0.2775)1,896nm — median 0.1386 (q25–q75 0.09667–0.1719)1,911nm — median 0.0809 (q25–q75 0.05028–0.1104)1,925nm — median 0.05876 (q25–q75 0.03345–0.08529)1,940nm — median 0.05639 (q25–q75 0.03121–0.08205)1,954nm — median 0.06531 (q25–q75 0.03784–0.09263)1,968nm — median 0.08044 (q25–q75 0.04757–0.11)1,983nm — median 0.09975 (q25–q75 0.06128–0.132)1,997nm — median 0.1175 (q25–q75 0.07339–0.1516)2,012nm — median 0.1363 (q25–q75 0.0878–0.1726)2,026nm — median 0.1533 (q25–q75 0.1011–0.1907)2,040nm — median 0.1687 (q25–q75 0.1136–0.2067)2,055nm — median 0.1825 (q25–q75 0.1255–0.2215)2,069nm — median 0.1943 (q25–q75 0.1361–0.2331)2,083nm — median 0.2054 (q25–q75 0.1467–0.2445)2,098nm — median 0.2168 (q25–q75 0.1577–0.2566)2,112nm — median 0.2273 (q25–q75 0.1673–0.2664)2,127nm — median 0.2368 (q25–q75 0.1755–0.2756)2,141nm — median 0.2444 (q25–q75 0.1827–0.2828)2,155nm — median 0.2505 (q25–q75 0.1903–0.289)2,170nm — median 0.2562 (q25–q75 0.1962–0.2941)2,184nm — median 0.2606 (q25–q75 0.2008–0.298)2,199nm — median 0.2649 (q25–q75 0.2053–0.3016)2,213nm — median 0.2666 (q25–q75 0.2069–0.303)2,227nm — median 0.2657 (q25–q75 0.2058–0.3021)2,242nm — median 0.2615 (q25–q75 0.2012–0.2982)2,256nm — median 0.2536 (q25–q75 0.1927–0.2909)2,271nm — median 0.2436 (q25–q75 0.1831–0.2813)2,285nm — median 0.2339 (q25–q75 0.1737–0.2723)2,299nm — median 0.2251 (q25–q75 0.1651–0.2637)2,314nm — median 0.2165 (q25–q75 0.1562–0.2554)2,328nm — median 0.2086 (q25–q75 0.1489–0.2487)2,342nm — median 0.2008 (q25–q75 0.1421–0.2415)2,357nm — median 0.1918 (q25–q75 0.1343–0.2332)2,371nm — median 0.1831 (q25–q75 0.1265–0.2244)2,386nm — median 0.1723 (q25–q75 0.1172–0.214)2,400nm — median 0.1617 (q25–q75 0.1078–0.2024)

Sampling

How many observations and spectral channels were exported, and how the wavelength axis is spaced. Reading guide

Wavelengths
?Number of spectral channels. A channel can represent wavelength, wavenumber or another feature axis.
2,001
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
400–2,400 nm
Mean spacing
?Average difference between adjacent spectral-axis coordinates; compare only within the same unit.
1 nm
Grid
?Uniform means adjacent axis spacings are approximately equal. An irregular grid may need care when applying derivatives.
uniform
Observations
?Exported spectral rows in this source, including repeated measurements when present.
1,971

Signal & quality

Signal level and roughness summaries. These depend on the signal representation and are not instrument acceptance tests. Reading guide

Value range
?Minimum and maximum recorded spectral values, in the original signal representation.
-0.169 – 0.576
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
0.00365 – 0.432
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
0.2674
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
534.9
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
0.4288
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
9.1207e-06
Roughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR.
2.9e+04
Roughness S/N proxy dB
?20 log10 of the roughness signal-to-noise proxy. Units are decibels; compare only compatible signal representations.
9e+01 dB
Dynamic range
?Maximum minus minimum of the mean spectrum. Its magnitude depends on the signal representation.
0.429
Smoothness
?Mean per-spectrum RMS of second differences, in signal units. Smaller values indicate smoother spectra under this protocol.
0.0003405
Saturated
?Fraction at the observed global maximum; a heuristic indicator, not a comparison with known detector limits.
0.0%
X-outliers
?Number flagged by the qualification outlier method. An unusual spectrum can be valid and should not be discarded automatically.
902

Integrity & artefacts

Missing values, narrow spikes and abrupt jumps to investigate in the original spectra. Reading guide

NaN ratio
?Missing spectral cells divided by all spectral cells, displayed as a percentage.
0.00%
Inf count
?Number of positive or negative infinite spectral values; investigate invalid calculations or export.
0
Zero ratio
?Exactly zero spectral cells divided by all cells. Zero can be a valid measurement and is not automatically missing.
0.00%
Spike count
?Local narrow peaks flagged by the second-difference heuristic; real sharp spectral bands may also be flagged.
181,085
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
4.60%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
133,078
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
3.38%
Clip fraction
?Fraction of finite cells near the observed global minimum or maximum; inspect detector limits before concluding saturation.
0.00%

Shape & reference

Variation relative to this dataset's mean spectrum; the mean is not an independently measured calibration reference. Reading guide

Baseline slope
?Linear slope fitted to the mean spectrum over an axis normalized to 0–1. It describes total baseline change, not change per physical axis unit.
0.0050807
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.00033434
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.0016331
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
0.03917
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
0.14092
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.07192
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.29432
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
0.076795
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
0.27552
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
0.044935
Xcorr lag p95
?95th percentile of the absolute cross-correlation shift relative to the mean spectrum, in spectral channels.
0

Outliers & repeatability

Unusual spectra and within-ID dispersion. Repeated IDs do not by themselves establish technical repetitions. Reading guide

PCA Q p95/median
?Q (squared prediction error) is variation left outside the retained PCA subspace. The displayed ratio compares its 95th percentile with its median.
5
Hotelling T2 p95/median
?Hotelling T² measures distance within the retained PCA subspace, scaled by component variance. Ratio of the 95th percentile to the median.
6
Mahalanobis H p95/median
?Distance from the PCA-score center after variance scaling. Ratio of the 95th percentile to the median; large values identify relatively extreme spectra.
2.4
Repeat groups
?Number of IDs with several observations. Source documentation is needed to decide whether these are technical repeats, positions or time points.
0

Dimensionality (PCA)

Principal component analysis (PCA) compresses correlated wavelengths into components. This describes spectral variation, without using prediction targets. Reading guide

Effective rank
?Entropy-based summary of the variance distribution across components. Larger values indicate variation spread across more dimensions.
1.3
PCs → 95% var
?Number of principal components needed to explain 95% of spectral variance, when reached by the computed projection.
2
PCs → 99% var
?Number of principal components needed to explain 99% of spectral variance, when reached by the computed projection.
3
Top-10 cum. var
?Fraction of spectral variance explained by up to the first ten computed principal components, displayed as a percentage.
100.0%
Computed metric scores 30highest alert 1.00

Value is the measured quantity; alert score is its heuristic mapping to 0–1. Levels are weak below 0.42, medium from 0.42, and strong from 0.72. These are display bands, not calibrated acceptance thresholds. A dash means unavailable, never zero. Possible causes are suggestions to investigate. Use each metric’s ? control for its meaning and scoring: hover for a hint, or expand it with a tap, Enter or Space.

FamilyComputed metricValueAlert scoreHeuristic levelDescriptive interpretationPossible causes to verifyCalculation / scoring
Data integrityInvalid/masked cell count (owner report)
?Count of cells reported unavailable by the native owner under its null or validity mask. This count is distinct from the historical NaN ratio; consult the recorded population and denominator. Scoring: No alert mapping is defined for this metric; an unavailable score does not mean a zero measured value. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.missing_cells		——not calculableNot enough information to score this metric on this dataset.Missing data or validity mask; not evidence of an acquisition causeNative Preflight count of cells unavailable under x/null and valid_mask; denominator stays in native_metric.denominators.n_cells. Not legacy NaN ratio.
Data integrityNaN ratio
?Missing spectral cells divided by all spectral cells, displayed as a percentage. Scoring: alert = min(1, nan_ratio / 0.05). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.nan_ratio		0%0.00weakFull spectrumAcquisition/export errorcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Data integrityInf count
?Number of positive or negative infinite spectral values; investigate invalid calculations or export. Scoring: alert = min(1, inf_count / 1). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.inf_count		00.00weakNormalInvalid calculationscount(isinf(X))alert = min(1, inf_count / 1)
Data integrityZero ratio
?Exactly zero spectral cells divided by all cells. Zero can be a valid measurement and is not automatically missing. Scoring: alert = min(1, zero_ratio / 0.05). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.zero_ratio		0%0.00weakNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Overall amplitudeMean reflectance
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations. Scoring: alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.mean_reflectance		0.267370.26weakToo darkBackground, geometrymean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Overall amplitudeArea under curve
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit. Scoring: alert reuses baseline/shape drift because area scale depends on axis and units. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.area_under_curve		534.920.26weakNormalProbe distancetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Overall amplitudePeak-to-peak (PTP)
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum. Scoring: alert increases when dynamic range is abnormally flat. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.peak_to_peak		0.428750.00weakStrong variabilitySaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Overall amplitudeVariance
?Variance of all finite spectral cells, in squared signal units. It combines variation across observations and channels; a small value can describe a flat signal. Scoring: alert increases when variance/dynamic range is abnormally flat. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.variance		0.0226580.00weakNormal or heterogeneousBad contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
NoiseRoughness sigma proxy
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise. Scoring: alert = noise_rms / signal_scale, saturated at 5%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.roughness_sigma_proxy		9.1207e-060.00weakStableLamp, detectormedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
NoiseRoughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR. Scoring: alert decreases with SNR dB; >=40 dB is treated as low alert. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.roughness_signal_to_noise_proxy		293160.00weakGood signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
NoiseBandwise roughness S/N proxy
?Minimum channel-wise ratio of absolute mean signal to local second-difference roughness. A smaller ratio identifies a weak or rough spectral region; genuine narrow bands and near-zero signal can also lower it. This is not certified instrument SNR. Scoring: alert decreases with worst-band SNR dB; >=35 dB is treated as low alert. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.bandwise_roughness_signal_to_noise_proxy_min		118.190.00weakReliable zoneDetectormin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Local artifactsSpike count
?Local narrow peaks flagged by the second-difference heuristic; real sharp spectral bands may also be flagged. Scoring: alert follows spike_rate, saturated at 1%. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.spike_count		181,0851.00strongArtifactsCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Local artifactsSpike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage. Scoring: alert = min(1, spike_rate / 0.01). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.spike_rate		4.6%1.00strongSuspicious spectrumInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Local artifactsJump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins. Scoring: alert follows jump_rate, saturated at 1%. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.jump_count		133,0781.00strongDetector connectionSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Local artifactsJump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage. Scoring: alert = min(1, jump_rate / 0.01). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.jump_rate		3.38%1.00strongSpectral problemCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Local artifactsClip fraction
?Fraction of finite cells near the observed global minimum or maximum; inspect detector limits before concluding saturation. Scoring: alert = min(1, clip_fraction / 0.01). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.clip_fraction		5.07e-05%0.00weakNormalDetector saturatedfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Spectral formBaseline slope
?Linear slope fitted to the mean spectrum over an axis normalized to 0–1. It describes total baseline change, not change per physical axis unit. Scoring: alert = abs(slope / signal_scale), saturated at 0.5. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
shape.baseline_slope		0.00508070.02weakStableIlluminationlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Spectral formCurvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation. Scoring: alert = curvature_rms / signal_scale, saturated at 1%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
shape.curvature_rms		0.000334340.08weakSmoothBackground, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Spectral formD1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts. Scoring: alert = d1_rms / signal_scale, saturated at 5%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
shape.d1_rms		0.00163310.08weakFlatBiology or artifactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Multivariate outliersPCA Q (SPE)
?Q (squared prediction error) is variation left outside the retained PCA subspace. The displayed ratio compares its 95th percentile with its median. Scoring: alert = min(1, pca_q_ratio / 8). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.pca_q_ratio		4.9840.62mediumAtypical spectrumArtifact, mixturep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Multivariate outliersHotelling T²
?Hotelling T² measures distance within the retained PCA subspace, scaled by component variance. Ratio of the 95th percentile to the median. Scoring: alert = min(1, hotelling_t2_ratio / 8). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.hotelling_t2_ratio		5.9790.75strongExtreme but consistentNatural variabilityp95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Multivariate outliersMahalanobis H
?Distance from the PCA-score center after variance scaling. Ratio of the 95th percentile to the median; large values identify relatively extreme spectra. Scoring: alert = min(1, mahalanobis_h_ratio / 4). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.mahalanobis_h_ratio		2.44520.61mediumGlobal outlierDifferent domainp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparison to average spectrumRMS to mean spectrum
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value. Scoring: alert = RMS_p95 / signal_scale, saturated at 25%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
reference.rms_to_mean_spectrum_p95		0.140921.00strongDifferent spectrumDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparison to average spectrumSpectral Angle Mapper (SAM)
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS. Scoring: alert = min(1, SAM_p95 / 0.35 rad). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
reference.sam_to_mean_spectrum_p95		0.294320.84strongDifferent shapeBackground, geometryp95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RepeatabilityRMS intra-ID
?Within-ID root mean square deviation from the group's mean spectrum, in signal units. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = RMS_intra_ID / signal_scale, saturated at 10%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.rms_intra_id		——not calculableNot enough information to score this metric on this dataset.Positioningmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RepeatabilitySAM intra-ID
?Within-ID spectral angle to the group's mean spectrum, in radians. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = min(1, SAM_intra_ID / 0.15 rad). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.sam_intra_id		——not calculableNot enough information to score this metric on this dataset.Acquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RepeatabilityCV intra-ID
?Within-ID coefficient of variation: standard deviation relative to absolute mean; unstable near zero signal. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = min(1, CV_intra_ID / 0.25). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.cv_intra_id		——not calculableNot enough information to score this metric on this dataset.Operatormedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure of the datasetPCA score density
?Inverse median distance to nearby observations in retained PCA-score space. Larger raw values mean more closely spaced observations; scale depends on the PCA representation. The alert uses density variation, so raw density alone does not establish an anomaly. Scoring: alert follows density_cv/profile structure complexity, not raw density alone. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.pca_score_density		6.52260.99strongSubpopulationsDifferent batches1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure of the datasetkNN distance ratio (not LOF)
?95th percentile of mean k-nearest-neighbor distance divided by the population median of that distance, in PCA-score space. Values above 1 indicate an upper tail with more isolated observations; valid rare spectra can also be isolated. This distance ratio is not the Local Outlier Factor algorithm. Scoring: alert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.knn_distance_ratio_p95		2.96390.98strongIsolated spectrumRare casesp95(mean kNN distance / median population mean kNN distance) in PCA-score space; not LOFalert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2)
Structure of the datasetIsolation Forest score
?95th percentile of the negated Isolation Forest score in retained PCA-score space. Larger raw scores indicate easier isolation under that model; the scale is implementation-dependent. The displayed alert reuses structure complexity rather than directly mapping this raw score. Scoring: alert follows structure complexity; raw score is implementation-dependent. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.isolation_forest_score_p95		0.57770.99strongAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source trans_spec.csv: 800 of 1,971 source observations are plotted. PC1 captures 94.0% and PC2 3.7% of the reported spectral variance: 97.7% together; 2.3% remains outside this view.

Principal component analysis (PCA) summarizes spectral differences without using targets. The horizontal PC1 axis captures the largest variation; vertical PC2 captures the next largest direction of variation. Each dot is one observation; repeated measurements need not be distinct samples. Scores are projection coordinates, not wavelengths or target values. Nearby dots have similar projections; separate groups or isolated dots are leads to inspect in the original spectra and acquisition metadata. Overlapping dots can differ in omitted dimensions. The dots have no class or batch labels, so this view cannot identify groups, confirm defective observations, explain a chemical cause or measure prediction accuracy.

trans_spec.csv PCA score plot-10-50510-4-202PC1 -0.7239 · PC2 -0.5457PC1 -0.5854 · PC2 -0.4031PC1 -0.9182 · PC2 -0.3434PC1 -2.203 · PC2 -0.2702PC1 -2.201 · PC2 0.5271PC1 -1.939 · PC2 0.7521PC1 -1.64 · PC2 0.4162PC1 -2.842 · PC2 0.172PC1 -1.491 · PC2 -0.06431PC1 -1.776 · PC2 0.00881PC1 -0.6934 · PC2 -0.2711PC1 -1.295 · PC2 -0.3008PC1 -0.8562 · PC2 -0.1539PC1 -1.188 · PC2 -0.464PC1 -0.3934 · PC2 0.8448PC1 -1.035 · PC2 0.8139PC1 -1.636 · PC2 0.8218PC1 -3.211 · PC2 0.6887PC1 -1.421 · PC2 0.2758PC1 -1.285 · PC2 0.4301PC1 -1.563 · PC2 0.2691PC1 -3.372 · PC2 0.313PC1 -3.086 · PC2 0.3252PC1 -2.364 · PC2 0.2767PC1 -2.59 · PC2 0.01991PC1 -1.407 · PC2 -0.3149PC1 -1.489 · PC2 -0.3571PC1 -1.328 · PC2 -0.326PC1 -1.665 · PC2 -0.3003PC1 -1.475 · PC2 -0.1874PC1 -1.13 · PC2 -0.3618PC1 -1.152 · PC2 -0.3002PC1 -1.398 · PC2 -0.397PC1 -1.372 · PC2 0.05495PC1 -1.393 · PC2 0.4614PC1 -1.768 · PC2 0.8725PC1 -2.119 · PC2 0.8142PC1 -1.958 · PC2 0.795PC1 -1.031 · PC2 -0.4069PC1 -1.105 · PC2 -0.4008PC1 -0.4561 · PC2 -0.5017PC1 -1.71 · PC2 -0.5466PC1 -0.3596 · PC2 -0.776PC1 -2.291 · PC2 0.4082PC1 -1.41 · PC2 0.01748PC1 -1.41 · PC2 -0.2237PC1 -1.658 · PC2 -0.1601PC1 -1.252 · PC2 0.4675PC1 -1.123 · PC2 0.3577PC1 0.0241 · PC2 -0.3091PC1 -1.675 · PC2 -0.4306PC1 -1.185 · PC2 0.1035PC1 -1.318 · PC2 -0.1308PC1 -1.556 · PC2 -0.189PC1 -1.448 · PC2 0.08687PC1 -1.108 · PC2 -0.08116PC1 -3.136 · PC2 0.7586PC1 -2.94 · PC2 0.9088PC1 -1.843 · PC2 0.8176PC1 -1.853 · PC2 0.8784PC1 -1.096 · PC2 0.893PC1 -1.971 · PC2 -0.01708PC1 -1.702 · PC2 0.1351PC1 -0.5724 · PC2 -0.432PC1 -0.8621 · PC2 -0.4799PC1 -0.1969 · PC2 -0.1699PC1 -0.7459 · PC2 -0.2802PC1 0.4892 · PC2 -0.5064PC1 0.7982 · PC2 -0.214PC1 -0.3268 · PC2 -0.4157PC1 -2.302 · PC2 0.3144PC1 -3.615 · PC2 0.277PC1 -1.28 · PC2 0.3049PC1 -1.116 · PC2 0.006793PC1 -0.5926 · PC2 -0.02023PC1 -2.022 · PC2 0.4123PC1 -0.772 · PC2 0.627PC1 -1.494 · PC2 -0.3123PC1 -1.122 · PC2 -0.4353PC1 -0.2463 · PC2 -0.5123PC1 -0.364 · PC2 -0.1755PC1 -0.7192 · PC2 -0.2242PC1 -3.102 · PC2 0.1071PC1 -2.802 · PC2 0.1118PC1 -2.289 · PC2 -0.116PC1 -2.748 · PC2 -0.08273PC1 -2.807 · PC2 -0.02104PC1 -3.185 · PC2 0.1886PC1 -0.6925 · PC2 -0.5678PC1 0.7889 · PC2 -0.4409PC1 0.336 · PC2 -0.2716PC1 -0.2445 · PC2 -0.5023PC1 -0.8208 · PC2 -0.01411PC1 -0.3257 · PC2 0.03823PC1 -1.676 · PC2 0.4252PC1 -1.834 · PC2 -0.06432PC1 -2.157 · PC2 0.12PC1 -0.4958 · PC2 -0.08348PC1 0.6746 · PC2 -0.0996PC1 0.0887 · PC2 0.02216PC1 -0.5355 · PC2 0.1612PC1 0.5513 · PC2 0.2271PC1 -0.3292 · PC2 0.4028PC1 -1.399 · PC2 -0.1478PC1 -1.269 · PC2 -0.224PC1 -1.54 · PC2 0.1568PC1 0.06514 · PC2 -0.133PC1 -2.127 · PC2 0.1521PC1 -1.994 · PC2 0.198PC1 -1.927 · PC2 0.356PC1 -0.8136 · PC2 -0.3393PC1 -1.771 · PC2 0.4382PC1 0.02786 · PC2 -0.4122PC1 -1.903 · PC2 0.4542PC1 -2.565 · PC2 0.643PC1 -2.108 · PC2 0.6707PC1 -1.98 · PC2 0.9068PC1 -0.7684 · PC2 0.6619PC1 -1.002 · PC2 -0.1194PC1 -0.5782 · PC2 0.1438PC1 -1.902 · PC2 0.05549PC1 -1.489 · PC2 0.1803PC1 -1.526 · PC2 0.4585PC1 -0.5199 · PC2 0.2195PC1 -0.8294 · PC2 0.614PC1 -0.6238 · PC2 0.6702PC1 -0.8812 · PC2 0.6746PC1 -1.32 · PC2 0.7765PC1 -1.653 · PC2 0.3983PC1 -1.835 · PC2 0.3155PC1 -2.285 · PC2 0.5293PC1 -1.232 · PC2 0.06299PC1 -0.4962 · PC2 0.5101PC1 -0.8883 · PC2 0.5218PC1 -1.389 · PC2 0.326PC1 -1.291 · PC2 1.055PC1 -1.459 · PC2 1.072PC1 0.0686 · PC2 0.6727PC1 -1.383 · PC2 0.6566PC1 -0.7182 · PC2 0.3285PC1 -0.6757 · PC2 0.1611PC1 -0.6263 · PC2 -0.2973PC1 -1.64 · PC2 0.07713PC1 -0.2468 · PC2 -0.06391PC1 -0.2351 · PC2 -0.1794PC1 -0.2627 · PC2 0.08594PC1 -0.2366 · PC2 -0.1939PC1 -4.404 · PC2 1.028PC1 -1.386 · PC2 0.931PC1 -1.301 · PC2 0.9539PC1 -0.5761 · PC2 0.5779PC1 -0.6585 · PC2 -0.4865PC1 -0.6225 · PC2 -0.04316PC1 -1.327 · PC2 -0.02353PC1 -0.8526 · PC2 -0.2724PC1 -1.93 · PC2 0.4244PC1 -0.7985 · PC2 -0.45PC1 -0.7166 · PC2 -0.4506PC1 -0.2362 · PC2 -0.3224PC1 -1.801 · PC2 0.9637PC1 -1.37 · PC2 0.9348PC1 -2.986 · PC2 0.9351PC1 -1.576 · PC2 -0.0151PC1 -0.3285 · PC2 -0.4694PC1 -0.07058 · PC2 -0.3293PC1 -1.514 · PC2 0.5555PC1 -1.426 · PC2 0.7916PC1 -0.7289 · PC2 0.8887PC1 -2.407 · PC2 1.165PC1 -2.029 · PC2 0.3406PC1 -0.8754 · PC2 -0.377PC1 -0.1413 · PC2 -0.3223PC1 -0.4651 · PC2 0.129PC1 -0.83 · PC2 -0.6311PC1 -0.3929 · PC2 -0.4492PC1 -0.9771 · PC2 -0.3915PC1 -0.3731 · PC2 -0.643PC1 4.178 · PC2 -0.1656PC1 5.087 · PC2 -0.2999PC1 5.219 · PC2 0.9268PC1 -2.684 · PC2 -0.6397PC1 -3.626 · PC2 0.1246PC1 -4.562 · PC2 -0.2759PC1 -1.46 · PC2 -2.025PC1 6.161 · PC2 0.3411PC1 6.47 · PC2 0.5198PC1 -5.733 · PC2 0.5339PC1 -5.218 · PC2 0.365PC1 -3.377 · PC2 0.08747PC1 -6.474 · PC2 0.9072PC1 -2.167 · PC2 -0.6357PC1 -0.7482 · PC2 -0.7027PC1 -3.122 · PC2 -0.2374PC1 -3.906 · PC2 -0.3594PC1 -4.689 · PC2 0.2028PC1 -2.199 · PC2 0.1761PC1 4.154 · PC2 -0.2467PC1 4.275 · PC2 -0.6006PC1 -2.393 · PC2 -0.6946PC1 -0.4498 · PC2 0.3511PC1 -0.7264 · PC2 0.4545PC1 -2.53 · PC2 0.2761PC1 -0.7412 · PC2 -0.001449PC1 -2.38 · PC2 0.3201PC1 -1.722 · PC2 -0.2597PC1 -1.388 · PC2 -0.4986PC1 -0.4889 · PC2 -1.261PC1 -2.326 · PC2 -0.1333PC1 -1.273 · PC2 -0.3609PC1 -1.444 · PC2 0.01051PC1 5.287 · PC2 0.8654PC1 5.247 · PC2 0.739PC1 7.804 · PC2 1.03PC1 7.644 · PC2 0.9658PC1 -1.192 · PC2 -0.4561PC1 -2.327 · PC2 -0.03328PC1 -2.894 · PC2 0.4539PC1 -2.495 · PC2 -0.6882PC1 -1.554 · PC2 -0.1198PC1 -2.804 · PC2 0.701PC1 -0.3082 · PC2 -0.5621PC1 0.007848 · PC2 -0.4715PC1 -0.7105 · PC2 -0.5093PC1 -3.023 · PC2 0.06194PC1 -3.224 · PC2 0.1637PC1 -3.491 · PC2 0.3843PC1 -1.429 · PC2 -0.4807PC1 -1.785 · PC2 0.02816PC1 -3.546 · PC2 -0.009745PC1 -2.845 · PC2 -0.2066PC1 -0.4665 · PC2 -0.3158PC1 -0.8683 · PC2 -0.379PC1 -1.579 · PC2 0.06808PC1 -0.5921 · PC2 -0.517PC1 -1.959 · PC2 -0.1048PC1 -2.222 · PC2 0.2245PC1 -1.128 · PC2 0.2777PC1 -0.1605 · PC2 0.1753PC1 -1.57 · PC2 0.4656PC1 -0.9897 · PC2 -1.123PC1 -2.333 · PC2 0.2337PC1 -0.5035 · PC2 -0.9228PC1 -5.356 · PC2 0.7609PC1 -2.565 · PC2 -0.3174PC1 -0.7969 · PC2 0.2742PC1 -4.31 · PC2 0.7184PC1 -8.229 · PC2 0.3434PC1 -4.265 · PC2 0.6906PC1 -1.531 · PC2 -0.489PC1 -2.418 · PC2 -0.4447PC1 -3.265 · PC2 -0.7955PC1 -1.111 · PC2 -0.7294PC1 -1.908 · PC2 -0.4585PC1 -4.382 · PC2 0.2171PC1 -2.926 · PC2 0.4972PC1 -3.264 · PC2 0.2779PC1 -3.927 · PC2 0.6936PC1 -1.506 · PC2 -0.0166PC1 -2.621 · PC2 0.4701PC1 -3.614 · PC2 0.2271PC1 -3.842 · PC2 0.8089PC1 -2.758 · PC2 0.4835PC1 -1.352 · PC2 0.1925PC1 -4.597 · PC2 0.9465PC1 -0.7641 · PC2 0.05603PC1 -3.302 · PC2 0.522PC1 -0.04998 · PC2 -0.08721PC1 -0.8383 · PC2 0.1623PC1 -2.713 · PC2 0.3324PC1 -2.552 · PC2 0.7684PC1 -4.71 · PC2 1.005PC1 -1.039 · PC2 0.5318PC1 -3.224 · PC2 0.7496PC1 -4.563 · PC2 1.191PC1 -4.781 · PC2 1.233PC1 -3.666 · PC2 0.4682PC1 -4.642 · PC2 0.8175PC1 -2.847 · PC2 0.5322PC1 -4.709 · PC2 1.199PC1 -3.822 · PC2 1.377PC1 -3.739 · PC2 1.017PC1 -2.763 · PC2 0.3729PC1 -2.207 · PC2 0.6271PC1 -1.038 · PC2 -0.1959PC1 0.9765 · PC2 -0.2643PC1 -0.4609 · PC2 -0.1181PC1 3.915 · PC2 0.05713PC1 2.214 · PC2 -0.1681PC1 -1.069 · PC2 0.5606PC1 1.691 · PC2 0.05242PC1 5.89 · PC2 0.6421PC1 5.513 · PC2 0.554PC1 5.456 · PC2 0.8298PC1 -3.229 · PC2 0.3568PC1 6.317 · PC2 0.2385PC1 -1.837 · PC2 0.1784PC1 -1.794 · PC2 0.1466PC1 -0.7419 · PC2 -0.2032PC1 8.03 · PC2 1.079PC1 8.157 · PC2 1.369PC1 8.555 · PC2 1.746PC1 6.044 · PC2 0.07771PC1 -3.433 · PC2 0.4303PC1 -2.434 · PC2 0.0724PC1 -1.323 · PC2 0.5853PC1 -0.5055 · PC2 0.3633PC1 -1.437 · PC2 0.2616PC1 -0.9169 · PC2 -0.5388PC1 -5.455 · PC2 1.333PC1 -2.977 · PC2 -0.2706PC1 -3.315 · PC2 0.5071PC1 -5.461 · PC2 1.158PC1 -4.668 · PC2 1.081PC1 -4.227 · PC2 1.045PC1 -3.416 · PC2 0.9691PC1 -5.858 · PC2 1.525PC1 8.227 · PC2 0.8657PC1 8.28 · PC2 0.9101PC1 8.348 · PC2 1.014PC1 5.642 · PC2 0.1835PC1 6.921 · PC2 0.4746PC1 6.544 · PC2 0.1211PC1 7.809 · PC2 0.8153PC1 6.405 · PC2 0.2952PC1 6.711 · PC2 0.474PC1 7.866 · PC2 0.614PC1 0.7116 · PC2 0.3688PC1 -0.4173 · PC2 0.0799PC1 2.43 · PC2 -0.6709PC1 0.321 · PC2 -1.105PC1 -0.3873 · PC2 0.06024PC1 1.596 · PC2 0.0926PC1 1.096 · PC2 -0.3837PC1 3.626 · PC2 0.0383PC1 -2.294 · PC2 -0.8546PC1 0.02237 · PC2 -0.9273PC1 -1.87 · PC2 -0.09PC1 -0.5729 · PC2 -0.2395PC1 -0.167 · PC2 -0.1398PC1 0.6239 · PC2 -0.7013PC1 -0.5601 · PC2 -0.5678PC1 0.3368 · PC2 -0.1258PC1 -0.6292 · PC2 0.3641PC1 0.3862 · PC2 0.3626PC1 -0.07577 · PC2 -0.02141PC1 -0.08965 · PC2 -0.1157PC1 -0.6177 · PC2 -0.1253PC1 2.227 · PC2 -0.2108PC1 -1.338 · PC2 -0.5573PC1 1.688 · PC2 -0.7568PC1 -1.246 · PC2 0.01191PC1 -0.4983 · PC2 -1.691PC1 -0.4461 · PC2 -1.196PC1 -1.328 · PC2 0.1774PC1 -0.04581 · PC2 0.2836PC1 -0.1308 · PC2 -0.09102PC1 -1.144 · PC2 0.1186PC1 -0.4776 · PC2 0.8153PC1 -0.4529 · PC2 0.1813PC1 0.01195 · PC2 -0.1632PC1 -0.2027 · PC2 -0.1963PC1 -0.6887 · PC2 -0.7578PC1 -2.496 · PC2 -1.009PC1 -2.185 · PC2 -0.139PC1 2.557 · PC2 -0.7735PC1 2.496 · PC2 -0.7544PC1 -0.5534 · PC2 -0.4557PC1 0.9731 · PC2 -0.55PC1 2.076 · PC2 -0.999PC1 0.1312 · PC2 -1.12PC1 -0.2821 · PC2 0.1456PC1 -1.978 · PC2 -0.617PC1 -2.492 · PC2 0.9933PC1 5.255 · PC2 -0.2033PC1 4.903 · PC2 -0.1362PC1 3.695 · PC2 -0.2341PC1 3.904 · PC2 -0.4384PC1 -1.314 · PC2 0.2312PC1 -0.09003 · PC2 -0.4855PC1 -0.1303 · PC2 -0.3524PC1 -3.165 · PC2 -0.8231PC1 -2.047 · PC2 -0.7327PC1 -2.437 · PC2 -0.8534PC1 -0.6086 · PC2 -0.4968PC1 -2.159 · PC2 -0.4183PC1 -1.059 · PC2 -0.1035PC1 0.09002 · PC2 0.4841PC1 4.532 · PC2 -0.9034PC1 4.838 · PC2 -0.7882PC1 0.0889 · PC2 -0.8044PC1 0.04514 · PC2 -0.8533PC1 -0.8637 · PC2 0.3003PC1 -2.803 · PC2 -0.4707PC1 -2.174 · PC2 0.44PC1 -3.6 · PC2 -0.2829PC1 -1.35 · PC2 0.2824PC1 1.334 · PC2 0.05444PC1 4.773 · PC2 -0.8185PC1 5.198 · PC2 -0.3158PC1 -1.397 · PC2 0.1045PC1 -1.78 · PC2 0.2629PC1 1.239 · PC2 -0.9919PC1 -0.5802 · PC2 0.5043PC1 -0.4111 · PC2 0.2647PC1 2.731 · PC2 -0.4333PC1 3.117 · PC2 -0.7083PC1 0.878 · PC2 -1.067PC1 0.7986 · PC2 -0.8477PC1 -1.092 · PC2 0.6507PC1 1.321 · PC2 -0.6887PC1 -2.265 · PC2 0.4927PC1 0.7209 · PC2 -1.244PC1 -2.451 · PC2 0.4495PC1 0.6249 · PC2 -0.8542PC1 0.9448 · PC2 -0.9344PC1 -2.917 · PC2 -0.174PC1 -3.433 · PC2 -0.1662PC1 -1.847 · PC2 -0.7051PC1 -0.5811 · PC2 -0.04971PC1 4.794 · PC2 -0.6196PC1 5.041 · PC2 -0.4811PC1 -3.152 · PC2 0.5107PC1 -3.926 · PC2 0.395PC1 3.527 · PC2 -0.6417PC1 3.388 · PC2 -0.6295PC1 -4.182 · PC2 0.4679PC1 -1.558 · PC2 -0.1196PC1 -1.739 · PC2 -0.2462PC1 -1.554 · PC2 -0.2079PC1 -0.748 · PC2 -0.2047PC1 -0.8131 · PC2 -0.5779PC1 -1.893 · PC2 -0.1512PC1 -1.293 · PC2 -0.2643PC1 -1.57 · PC2 -0.5393PC1 -2.953 · PC2 0.4342PC1 -2.49 · PC2 0.1634PC1 -0.6782 · PC2 -0.2856PC1 -1.523 · PC2 0.139PC1 -4.355 · PC2 0.201PC1 -1.206 · PC2 -0.1514PC1 -0.01278 · PC2 -0.6133PC1 -2.86 · PC2 -0.1811PC1 -0.5289 · PC2 -0.2248PC1 0.6163 · PC2 0.0977PC1 -0.1072 · PC2 -0.1319PC1 -4.075 · PC2 0.646PC1 -4.329 · PC2 0.5941PC1 -1.629 · PC2 0.5916PC1 -1.717 · PC2 0.6021PC1 -3.492 · PC2 0.3535PC1 -0.5795 · PC2 -0.3026PC1 0.35 · PC2 -0.3576PC1 4.144 · PC2 -0.1983PC1 -2.451 · PC2 0.2402PC1 -0.09334 · PC2 0.06548PC1 0.9982 · PC2 0.1645PC1 0.3215 · PC2 -0.08168PC1 -0.9114 · PC2 -0.1173PC1 -1.61 · PC2 0.5001PC1 -1.678 · PC2 0.3543PC1 -1.159 · PC2 -0.7124PC1 -2.642 · PC2 0.3424PC1 -2.585 · PC2 0.3802PC1 -3.003 · PC2 0.2362PC1 5.292 · PC2 -0.2122PC1 6.474 · PC2 0.5469PC1 7.106 · PC2 0.4829PC1 -3.55 · PC2 0.34PC1 -2.554 · PC2 0.2575PC1 -2.302 · PC2 0.3904PC1 -2.556 · PC2 0.6149PC1 -0.9951 · PC2 -0.4405PC1 2.958 · PC2 -0.4463PC1 -2.01 · PC2 0.7291PC1 7.166 · PC2 0.7574PC1 7.197 · PC2 0.9782PC1 -2.763 · PC2 0.72PC1 -0.9052 · PC2 -0.2095PC1 -1.891 · PC2 -0.1403PC1 0.8959 · PC2 0.2555PC1 -2.493 · PC2 -0.2831PC1 -1.982 · PC2 0.2839PC1 -2.409 · PC2 1.075PC1 -0.3335 · PC2 -0.5184PC1 -1.859 · PC2 0.3572PC1 -0.9814 · PC2 -0.9006PC1 0.2048 · PC2 0.1477PC1 -0.4428 · PC2 0.162PC1 0.911 · PC2 0.251PC1 -0.8374 · PC2 0.2425PC1 -2.503 · PC2 0.4472PC1 -2.764 · PC2 0.2968PC1 -2.457 · PC2 0.3817PC1 -0.6208 · PC2 0.0226PC1 -0.7384 · PC2 0.2574PC1 -0.8297 · PC2 0.2037PC1 -0.5238 · PC2 0.4072PC1 -2.662 · PC2 0.8957PC1 6.546 · PC2 0.2891PC1 7.304 · PC2 0.6257PC1 -1.268 · PC2 0.565PC1 6.03 · PC2 0.07529PC1 5.626 · PC2 0.1098PC1 6.517 · PC2 -0.2745PC1 -2.608 · PC2 -0.1428PC1 7.128 · PC2 -0.04524PC1 3.479 · PC2 0.1678PC1 -2.223 · PC2 0.3162PC1 -3.537 · PC2 0.3912PC1 -3.143 · PC2 0.3575PC1 -1.337 · PC2 -0.3285PC1 -1.163 · PC2 0.04262PC1 -3.209 · PC2 0.4609PC1 0.1802 · PC2 -0.2204PC1 -2.869 · PC2 0.4839PC1 -2.336 · PC2 0.7067PC1 -0.7234 · PC2 -0.03652PC1 -1.655 · PC2 0.4144PC1 -2.43 · PC2 0.3737PC1 -2.997 · PC2 0.7777PC1 6.44 · PC2 0.1929PC1 6.825 · PC2 -0.05547PC1 6.486 · PC2 0.4143PC1 6.643 · PC2 0.04986PC1 -3.673 · PC2 0.4825PC1 6.401 · PC2 0.09421PC1 7.448 · PC2 0.07016PC1 6.401 · PC2 -0.3554PC1 1.718 · PC2 -0.2544PC1 1.243 · PC2 -0.3277PC1 -0.5167 · PC2 -0.03691PC1 -0.091 · PC2 -0.07952PC1 6.381 · PC2 0.4308PC1 1.932 · PC2 -0.3966PC1 1.293 · PC2 -0.4635PC1 1.108 · PC2 -0.3896PC1 2.17 · PC2 -0.2612PC1 7.145 · PC2 1.311PC1 5.283 · PC2 0.9384PC1 6.386 · PC2 0.9972PC1 4.794 · PC2 0.6745PC1 3.348 · PC2 0.1568PC1 5.309 · PC2 1.129PC1 5.035 · PC2 1.045PC1 6.432 · PC2 0.9221PC1 1.359 · PC2 -0.7977PC1 5.126 · PC2 0.4476PC1 5.363 · PC2 1.124PC1 1.105 · PC2 -0.8444PC1 4.609 · PC2 1.148PC1 1.904 · PC2 -0.5902PC1 4.352 · PC2 1.039PC1 2.021 · PC2 -0.7853PC1 2.085 · PC2 -0.5539PC1 4.784 · PC2 1.054PC1 2.974 · PC2 0.3527PC1 3.688 · PC2 0.3787PC1 4.886 · PC2 0.7914PC1 5.819 · PC2 0.9996PC1 5.217 · PC2 0.4957PC1 5.109 · PC2 0.7671PC1 4.898 · PC2 0.8298PC1 2.365 · PC2 0.7951PC1 3.495 · PC2 0.1375PC1 4.492 · PC2 0.5035PC1 6.257 · PC2 1.079PC1 1.923 · PC2 -0.6042PC1 5.77 · PC2 0.825PC1 1.642 · PC2 -0.3343PC1 5.682 · PC2 0.6886PC1 5.164 · PC2 0.591PC1 5.262 · PC2 0.9012PC1 3.413 · PC2 0.5576PC1 1.534 · PC2 -0.6102PC1 3.4 · PC2 0.3292PC1 6.366 · PC2 0.9645PC1 5.544 · PC2 0.8478PC1 4.754 · PC2 0.7649PC1 2.97 · PC2 -0.3331PC1 0.9817 · PC2 -0.742PC1 1.948 · PC2 -0.1969PC1 2.844 · PC2 -0.416PC1 4.246 · PC2 -0.1174PC1 4.274 · PC2 -0.3615PC1 2.206 · PC2 -1.311PC1 1.295 · PC2 -1.72PC1 -0.02409 · PC2 -1.378PC1 0.4657 · PC2 -1.489PC1 2.221 · PC2 -1.272PC1 5.853 · PC2 0.4868PC1 -0.4032 · PC2 -0.1927PC1 -0.7133 · PC2 -0.4246PC1 4.255 · PC2 0.2845PC1 5.301 · PC2 0.2864PC1 -1.54 · PC2 -0.4106PC1 4.143 · PC2 0.394PC1 5.006 · PC2 0.3894PC1 4.66 · PC2 0.317PC1 3.794 · PC2 0.874PC1 4.735 · PC2 1.082PC1 3.459 · PC2 0.7909PC1 4.668 · PC2 1.143PC1 1.28 · PC2 1.795PC1 1.618 · PC2 1.651PC1 1.543 · PC2 0.5984PC1 1.127 · PC2 0.7496PC1 -4.703 · PC2 0.1951PC1 -4.978 · PC2 0.5995PC1 0.229 · PC2 -0.1802PC1 0.1294 · PC2 -0.01638PC1 -0.3284 · PC2 -0.3794PC1 1.297 · PC2 -3.138PC1 -1.968 · PC2 -0.4433PC1 -1.613 · PC2 -0.388PC1 -0.6272 · PC2 -0.4031PC1 -1.491 · PC2 0.1328PC1 -0.9141 · PC2 -0.526PC1 -0.4179 · PC2 -1.437PC1 -1.348 · PC2 -1.281PC1 -0.496 · PC2 -1.279PC1 -0.3209 · PC2 -1.195PC1 -1.433 · PC2 -1.17PC1 0.525 · PC2 -1.991PC1 2.188 · PC2 -1.285PC1 0.8482 · PC2 -1.982PC1 -1.911 · PC2 -2.318PC1 0.5233 · PC2 -2.081PC1 -2.096 · PC2 0.4979PC1 -3.078 · PC2 0.495PC1 -1.226 · PC2 0.4753PC1 -0.5065 · PC2 0.3721PC1 -2.411 · PC2 -0.005076PC1 -2.22 · PC2 0.2646PC1 -3.255 · PC2 0.4679PC1 -3.796 · PC2 0.3563PC1 -1.97 · PC2 0.04741PC1 0.1604 · PC2 -0.5921PC1 2.218 · PC2 -0.6535PC1 -2.465 · PC2 0.4714PC1 -4.097 · PC2 0.3452PC1 -3.38 · PC2 0.2734PC1 -3.746 · PC2 0.4012PC1 -3.168 · PC2 0.4241PC1 -0.6491 · PC2 -0.006962PC1 -1.27 · PC2 0.08119PC1 -0.7137 · PC2 -0.2381PC1 -0.1408 · PC2 -0.2175PC1 -0.3248 · PC2 -0.534PC1 -2.517 · PC2 -0.07364PC1 0.2707 · PC2 -0.5687PC1 -1.783 · PC2 -0.6887PC1 -0.8205 · PC2 -0.07773PC1 -0.581 · PC2 -0.4631PC1 0.5928 · PC2 0.06701PC1 -1.514 · PC2 -0.1685PC1 -0.5016 · PC2 0.01624PC1 -0.5763 · PC2 -0.05208PC1 -0.4731 · PC2 0.2849PC1 -0.07425 · PC2 -0.6213PC1 1.565 · PC2 -0.5734PC1 0.04723 · PC2 -0.4834PC1 0.1911 · PC2 -0.4625PC1 1.291 · PC2 -0.525PC1 -0.5058 · PC2 -0.9921PC1 1.097 · PC2 -0.5928PC1 0.8014 · PC2 -0.9321PC1 1.051 · PC2 -1.028PC1 0.7479 · PC2 -0.7307PC1 -1.761 · PC2 -0.2517PC1 -0.3202 · PC2 -0.5865PC1 -2.38 · PC2 -0.05688PC1 -1.633 · PC2 -0.2453PC1 6.124 · PC2 -0.3227PC1 5.815 · PC2 -0.1512PC1 6.45 · PC2 -0.08536PC1 -0.6712 · PC2 -0.5072PC1 -1.183 · PC2 -0.6046PC1 -0.6333 · PC2 -0.6427PC1 -1.511 · PC2 -0.5276PC1 0.5395 · PC2 -0.675PC1 0.2926 · PC2 -0.9895PC1 0.9765 · PC2 -0.7043PC1 -0.8327 · PC2 -0.5329PC1 -1.532 · PC2 -0.6787PC1 -2.131 · PC2 -0.599PC1 -1.125 · PC2 -0.4436PC1 -2.637 · PC2 -0.4202PC1 -1.54 · PC2 -0.3556PC1 -1.717 · PC2 -0.4715PC1 -1.538 · PC2 -0.2763PC1 -0.6844 · PC2 -0.544PC1 6.2 · PC2 -0.2694PC1 7.34 · PC2 0.3661PC1 6.654 · PC2 -0.008973PC1 6.766 · PC2 0.1538PC1 6.728 · PC2 0.1697PC1 0.3227 · PC2 -0.598PC1 -2.176 · PC2 -0.1185PC1 -0.9695 · PC2 -0.05817PC1 -2.581 · PC2 0.05309PC1 -0.4162 · PC2 -0.2698PC1 -0.4254 · PC2 -0.5545PC1 0.2421 · PC2 -0.886PC1 0.7187 · PC2 -0.8115PC1 0.427 · PC2 -0.6395PC1 -1.946 · PC2 -0.3416PC1 -3.515 · PC2 -0.1576PC1 -2.591 · PC2 -0.2238PC1 -2.512 · PC2 -0.09594PC1 -2.855 · PC2 -0.142PC1 -2.589 · PC2 -0.3096PC1 -0.9071 · PC2 -0.6058PC1 5.098 · PC2 -0.5622PC1 5.31 · PC2 -0.4995PC1 5.192 · PC2 -0.2124PC1 -1.074 · PC2 0.07732PC1 -0.1268 · PC2 0.3831PC1 -0.7121 · PC2 0.4328PC1 0.1956 · PC2 -0.09034PC1 0.06159 · PC2 -0.1217PC1 0.5397 · PC2 -0.3595PC1 0.1287 · PC2 -0.803PC1 0.5016 · PC2 -0.277PC1 0.773 · PC2 -0.6158PC1 -0.9182 · PC2 -0.2403PC1 -1.614 · PC2 -0.1533PC1 -1.206 · PC2 -0.1862PC1 -1.771 · PC2 -0.2704PC1 -1.873 · PC2 -0.08013PC1 -0.1927 · PC2 0.4092PC1 -0.7745 · PC2 0.2744PC1 -0.3212 · PC2 -0.3193PC1 -0.4697 · PC2 0.1921PC1 6.228 · PC2 -0.04082PC1 5.901 · PC2 -0.03284PC1 5.36 · PC2 -0.05188PC1 6.202 · PC2 0.03006PC1 -0.9491 · PC2 0.1027PC1 -0.3813 · PC2 -0.1049PC1 -2.041 · PC2 0.2342PC1 -1.467 · PC2 0.2074PC1 -0.94 · PC2 -0.1962PC1 -1.833 · PC2 -0.2215PC1 -1.746 · PC2 -0.1125PC1 -0.8686 · PC2 -0.1135PC1 -2.491 · PC2 -0.01953PC1 -1.334 · PC2 -0.213PC1 0.7893 · PC2 -0.7441PC1 1.479 · PC2 -0.5759PC1 0.3826 · PC2 -0.8548PC1 -1.012 · PC2 0.01245PC1 -1.632 · PC2 0.2009PC1 -1.15 · PC2 0.3105PC1 -1.035 · PC2 0.3685PC1 5.706 · PC2 0.0451PC1 5.146 · PC2 -0.0541PC1 5.748 · PC2 -0.08883PC1 4.363 · PC2 -0.1682PC1 5.402 · PC2 -0.09362PC1 0.2984 · PC2 0.1434PC1 0.02024 · PC2 -0.06417PC1 -0.6799 · PC2 0.1297PC1 -0.4354 · PC2 0.1474PC1 0.9048 · PC2 -0.09568PC1 -1.441 · PC2 -0.2069PC1 -0.9625 · PC2 -0.3153PC1 -1.523 · PC2 -0.438PC1 -0.3905 · PC2 0.1785PC1 -1.152 · PC2 -0.06532PC1 6.269 · PC2 0.1181PC1 5.244 · PC2 -0.04585PC1 6.036 · PC2 0.3302PC1 5.786 · PC2 0.08977PC1 0.9178 · PC2 -0.4651PC1 0.3619 · PC2 -0.6515PC1 1.13 · PC2 -0.2567PC1 1.253 · PC2 -0.3013PC1 1.744 · PC2 -0.8795PC1 1.119 · PC2 -0.3363PC1 1.064 · PC2 -0.2558PC1 2.505 · PC2 -0.6677PC1 1.065 · PC2 -0.5351PC1 1.328 · PC2 -0.3017PC1 1.876 · PC2 -0.4829PC1 1.723 · PC2 -0.4921PC1 1.579 · PC2 -0.276PC1 2.079 · PC2 -0.2252PC1 1.627 · PC2 -0.7278PC1 1.837 · PC2 -0.2499PC1 1.532 · PC2 -0.2629PC1 0.2216 · PC2 0.01902PC1 1.037 · PC2 -0.2908PC1 3.135 · PC2 -0.4321PC1 2.488 · PC2 -0.6708PC1 2.952 · PC2 -0.2599PC1 2.596 · PC2 -0.4296PC1 1.619 · PC2 -0.6628PC1 2.057 · PC2 -0.7871PC1 2.54 · PC2 -0.6443PC1 3.573 · PC2 -0.9347PC1 (94.0%)PC2 (3.7%)800 scores
View plotted PCA coordinates

Point numbers identify rows in this displayed coordinate list, not original observation or sample IDs. Non-integer coordinates use up to five significant digits. Original IDs, component loadings, preprocessing details and the observation selection method are not supplied with this plot.

Plotted observation positions (not original sample IDs)
PointPC1 scorePC2 score
1-0.72392-0.54565
2-0.58543-0.40311
3-0.91822-0.34336
4-2.2032-0.27019
5-2.20140.52708
6-1.93890.75207
7-1.63950.4162
8-2.84240.172
9-1.4914-0.064308
10-1.77590.0088101
11-0.69338-0.27106
12-1.295-0.30077
13-0.85625-0.15389
14-1.1877-0.46399
15-0.393430.84476
16-1.03480.81385
17-1.63550.82178
18-3.21080.68869
19-1.42130.27577
20-1.2850.43015
21-1.56320.26912
22-3.37220.31298
23-3.08610.32521
24-2.3640.27669
25-2.59030.019912
26-1.4072-0.31486
27-1.489-0.35713
28-1.3283-0.32602
29-1.6647-0.3003
30-1.4747-0.1874
31-1.1301-0.36184
32-1.1519-0.30023
33-1.3981-0.39696
34-1.37240.054947
35-1.39260.46142
36-1.76840.8725
37-2.11880.81419
38-1.95830.79501
39-1.0312-0.40693
40-1.1046-0.40079
41-0.45608-0.50169
42-1.7095-0.54661
43-0.35961-0.776
44-2.2910.40817
45-1.40970.017484
46-1.4097-0.22373
47-1.6579-0.16007
48-1.25210.46754
49-1.12310.3577
500.0241-0.30913
51-1.6749-0.43058
52-1.18530.10349
53-1.318-0.13078
54-1.5564-0.18895
55-1.44780.08687
56-1.1081-0.081161
57-3.13610.75857
58-2.93970.90878
59-1.84310.81763
60-1.85270.87836
61-1.09550.89301
62-1.9708-0.017082
63-1.7020.13508
64-0.57242-0.43204
65-0.86212-0.47986
66-0.19693-0.16995
67-0.7459-0.28018
680.48922-0.50637
690.79817-0.21396
70-0.32678-0.41571
71-2.30170.31441
72-3.61490.27701
73-1.28040.30492
74-1.11620.0067929
75-0.59256-0.020233
76-2.02150.41229
77-0.771980.62701
78-1.4945-0.3123
79-1.1221-0.43527
80-0.24626-0.51231
81-0.36396-0.1755
82-0.71915-0.22417
83-3.10160.10707
84-2.80190.11184
85-2.2888-0.11604
86-2.7484-0.082734
87-2.8066-0.021041
88-3.18520.18855
89-0.69246-0.56781
900.78893-0.44093
910.336-0.27162
92-0.24445-0.50234
93-0.82082-0.014115
94-0.32570.03823
95-1.67580.42522
96-1.834-0.064316
97-2.15740.11999
98-0.4958-0.083476
990.67455-0.099604
1000.0887010.022156
101-0.535450.16117
1020.551320.22706
103-0.329240.40282
104-1.3985-0.14778
105-1.2686-0.224
106-1.540.15683
1070.065135-0.133
108-2.12710.15214
109-1.99440.19805
110-1.92680.35596
111-0.81356-0.33933
112-1.77080.43821
1130.027856-0.41216
114-1.90340.45418
115-2.56510.64299
116-2.10780.67074
117-1.97970.90683
118-0.768370.66186
119-1.0023-0.11936
120-0.578210.14382
121-1.90160.055493
122-1.48860.18033
123-1.52620.45854
124-0.519920.21947
125-0.829450.61396
126-0.623850.67022
127-0.881150.67465
128-1.32050.77653
129-1.65280.39825
130-1.83470.31546
131-2.28450.5293
132-1.2320.062986
133-0.49620.51014
134-0.88830.52182
135-1.38930.32603
136-1.29071.0553
137-1.45861.0718
1380.0686050.67269
139-1.38260.65657
140-0.718190.32855
141-0.675650.16106
142-0.62634-0.29734
143-1.64030.077134
144-0.24682-0.063911
145-0.23507-0.17941
146-0.262690.085935
147-0.23658-0.19386
148-4.40371.028
149-1.38580.931
150-1.30110.95387
151-0.576130.5779
152-0.65853-0.48651
153-0.62251-0.043158
154-1.3274-0.023529
155-0.85264-0.27244
156-1.93030.42443
157-0.79848-0.44996
158-0.71664-0.4506
159-0.23622-0.32238
160-1.80150.96367
161-1.36970.9348
162-2.9860.93505
163-1.5761-0.015102
164-0.32853-0.46945
165-0.070585-0.32931
166-1.51360.5555
167-1.42550.7916
168-0.728930.8887
169-2.4071.1655
170-2.02870.34056
171-0.87539-0.37701
172-0.1413-0.32235
173-0.465080.12899
174-0.82996-0.63105
175-0.39293-0.4492
176-0.97711-0.3915
177-0.37312-0.64302
1784.178-0.16558
1795.0871-0.29994
1805.21890.92678
181-2.6844-0.63973
182-3.62580.12464
183-4.5621-0.27586
184-1.4601-2.0254
1856.16110.34114
1866.47010.51978
187-5.73340.53394
188-5.21830.36496
189-3.3770.087475
190-6.47380.90719
191-2.1673-0.63565
192-0.74816-0.70266
193-3.1222-0.23736
194-3.9058-0.35935
195-4.68880.20281
196-2.19930.1761
1974.1543-0.24667
1984.2749-0.60056
199-2.3931-0.69462
200-0.449820.35111
201-0.726420.45453
202-2.52960.27611
203-0.7412-0.0014485
204-2.37980.32008
205-1.7216-0.25968
206-1.3877-0.49859
207-0.48893-1.2607
208-2.3264-0.13331
209-1.2734-0.36086
210-1.4440.010508
2115.28660.86545
2125.24660.73902
2137.80441.0303
2147.64360.96581
215-1.192-0.45608
216-2.3266-0.033278
217-2.89450.45391
218-2.4954-0.68819
219-1.5536-0.1198
220-2.80390.70095
221-0.30824-0.56209
2220.007848-0.47149
223-0.71048-0.50928
224-3.02330.061941
225-3.22410.16368
226-3.4910.38428
227-1.4287-0.48066
228-1.78470.028158
229-3.5456-0.0097452
230-2.845-0.20664
231-0.4665-0.31584
232-0.86835-0.37899
233-1.57850.068079
234-0.59206-0.51703
235-1.9594-0.1048
236-2.22160.22451
237-1.12750.27767
238-0.160470.17534
239-1.57040.46556
240-0.9897-1.1234
241-2.33270.23374
242-0.50353-0.92283
243-5.35640.76089
244-2.565-0.31735
245-0.796880.27424
246-4.31040.71845
247-8.22930.34339
248-4.2650.6906
249-1.5307-0.48895
250-2.4179-0.44474
251-3.2648-0.79554
252-1.1113-0.72938
253-1.9082-0.45851
254-4.38190.2171
255-2.92650.49723
256-3.26410.2779
257-3.92660.69361
258-1.5064-0.016602
259-2.62140.47006
260-3.61370.22712
261-3.84170.80891
262-2.75820.48346
263-1.3520.19253
264-4.59710.94652
265-0.764070.056029
266-3.30240.52204
267-0.049984-0.087212
268-0.838320.16233
269-2.71310.33237
270-2.55230.76836
271-4.70981.0052
272-1.03880.5318
273-3.22410.74964
274-4.56341.1908
275-4.78061.2333
276-3.66610.46824
277-4.64160.8175
278-2.84680.53221
279-4.70931.1993
280-3.82221.3769
281-3.73871.0169
282-2.7630.37289
283-2.20660.62709
284-1.0384-0.19589
2850.97654-0.26429
286-0.4609-0.11806
2873.91530.057129
2882.2139-0.16814
289-1.06910.56055
2901.69130.05242
2915.89050.64214
2925.51310.55401
2935.45610.82975
294-3.22910.3568
2956.31720.23854
296-1.83730.17839
297-1.79390.14659
298-0.74189-0.20319
2998.03041.0792
3008.15751.3692
3018.55531.7464
3026.04430.077713
303-3.4330.43025
304-2.43380.072396
305-1.32290.58528
306-0.505540.36334
307-1.43710.26156
308-0.9169-0.53876
309-5.45551.3329
310-2.9774-0.27064
311-3.31460.50712
312-5.46061.1578
313-4.66791.0813
314-4.22711.0452
315-3.41610.96906
316-5.85811.5251
3178.22680.86566
3188.28040.91009
3198.34811.0144
3205.64170.18348
3216.92050.47464
3226.5440.12114
3237.80950.81526
3246.40480.29524
3256.71110.47398
3267.86630.614
3270.711620.36881
328-0.417280.079901
3292.4302-0.67089
3300.32103-1.1049
331-0.387280.060244
3321.59580.092604
3331.0964-0.38368
3343.62610.038303
335-2.2941-0.85457
3360.022366-0.92731
337-1.8703-0.089999
338-0.57292-0.23951
339-0.16697-0.13984
3400.62394-0.70128
341-0.56014-0.56781
3420.33676-0.12583
343-0.62920.36411
3440.386180.36265
345-0.075772-0.021414
346-0.089655-0.1157
347-0.61771-0.12528
3482.2267-0.21075
349-1.3383-0.55732
3501.6882-0.75678
351-1.24570.011908
352-0.49827-1.6907
353-0.44612-1.1962
354-1.32820.1774
355-0.0458090.28363
356-0.13079-0.091019
357-1.1440.11859
358-0.477610.81527
359-0.452860.18134
3600.011949-0.16316
361-0.20271-0.19627
362-0.68874-0.75782
363-2.4959-1.0093
364-2.185-0.13903
3652.5574-0.77347
3662.4963-0.75438
367-0.55345-0.4557
3680.97313-0.55002
3692.0762-0.99898
3700.13122-1.1204
371-0.282120.14565
372-1.9782-0.617
373-2.4920.99333
3745.2549-0.20334
3754.9032-0.1362
3763.6954-0.23406
3773.9042-0.43838
378-1.31410.23116
379-0.090031-0.48545
380-0.13027-0.35238
381-3.1654-0.82313
382-2.0472-0.73269
383-2.4371-0.85336
384-0.60863-0.49683
385-2.159-0.41833
386-1.0594-0.10354
3870.0900210.48406
3884.5315-0.90338
3894.8379-0.78824
3900.088902-0.80438
3910.045136-0.85326
392-0.863650.30031
393-2.8032-0.47073
394-2.1740.43995
395-3.6002-0.28289
396-1.34960.28239
3971.33350.054436
3984.7728-0.8185
3995.1982-0.31578
400-1.39690.10454
401-1.780.26289
4021.2391-0.99188
403-0.580210.50434
404-0.41110.26468
4052.7306-0.43326
4063.1167-0.70829
4070.87795-1.0671
4080.79859-0.84774
409-1.0920.65073
4101.3206-0.68873
411-2.26540.49266
4120.72088-1.2436
413-2.45140.4495
4140.6249-0.85416
4150.94481-0.93443
416-2.9173-0.17395
417-3.4327-0.16617
418-1.847-0.70513
419-0.58111-0.049713
4204.7942-0.61957
4215.0405-0.48108
422-3.1520.51073
423-3.92570.39497
4243.5273-0.64175
4253.3884-0.6295
426-4.18170.46795
427-1.5581-0.11962
428-1.739-0.2462
429-1.5545-0.20795
430-0.74797-0.20468
431-0.81314-0.57787
432-1.8933-0.15116
433-1.2931-0.26434
434-1.5698-0.53935
435-2.95330.43418
436-2.49010.16341
437-0.67817-0.28558
438-1.52340.13905
439-4.35540.201
440-1.2061-0.15137
441-0.012776-0.61325
442-2.8603-0.18109
443-0.52888-0.22478
4440.616350.097701
445-0.10721-0.13195
446-4.07510.64603
447-4.32890.59412
448-1.62930.59158
449-1.7170.60213
450-3.49170.35349
451-0.57948-0.30259
4520.35-0.35758
4534.1441-0.19829
454-2.45140.24021
455-0.0933360.065481
4560.998240.16455
4570.32154-0.081684
458-0.9114-0.11731
459-1.60970.50014
460-1.67780.35429
461-1.1587-0.71244
462-2.64210.34238
463-2.58480.38019
464-3.00280.23625
4655.2924-0.21222
4666.4740.54685
4677.10640.48288
468-3.55030.33998
469-2.55430.25751
470-2.30240.39039
471-2.55620.61488
472-0.99508-0.44051
4732.9583-0.44626
474-2.00990.72906
4757.16550.75739
4767.19740.97823
477-2.76310.71995
478-0.90521-0.20946
479-1.8906-0.14027
4800.895920.25549
481-2.4933-0.28315
482-1.98240.28386
483-2.40871.0746
484-0.33353-0.51842
485-1.85850.35716
486-0.98136-0.90065
4870.204820.14771
488-0.442820.16201
4890.911030.25097
490-0.83740.24248
491-2.50320.44721
492-2.76360.29682
493-2.45740.38168
494-0.620780.022599
495-0.73840.25735
496-0.829720.20365
497-0.523790.40725
498-2.66190.89574
4996.5460.28907
5007.30390.62575
501-1.26750.56499
5026.02990.075288
5035.6260.10984
5046.517-0.27453
505-2.6077-0.14281
5067.1275-0.045242
5073.47880.16776
508-2.22320.31623
509-3.53730.39115
510-3.14270.35752
511-1.3365-0.32846
512-1.16340.042615
513-3.20920.46093
5140.18017-0.22038
515-2.86880.48385
516-2.3360.70669
517-0.72338-0.036524
518-1.65540.41444
519-2.43050.37372
520-2.99670.77768
5216.440.19292
5226.8247-0.05547
5236.48630.41433
5246.64330.049863
525-3.67320.48251
5266.40140.094212
5277.44780.070159
5286.4007-0.35537
5291.7177-0.25443
5301.2429-0.32771
531-0.51665-0.03691
532-0.091005-0.079517
5336.38120.43081
5341.9315-0.39661
5351.2927-0.4635
5361.1076-0.38958
5372.1698-0.2612
5387.14451.3113
5395.28290.93841
5406.38580.9972
5414.7940.67446
5423.34810.15678
5435.30921.1295
5445.03541.0454
5456.43230.92209
5461.3591-0.79768
5475.12630.44761
5485.36351.1243
5491.105-0.84444
5504.60931.1485
5511.9039-0.59022
5524.35181.0386
5532.021-0.78529
5542.0853-0.55387
5554.78431.0539
5562.97370.35269
5573.68850.37865
5584.88560.79145
5595.81940.99958
5605.21730.49571
5615.10890.76714
5624.89780.82975
5632.36470.7951
5643.49450.13749
5654.49250.50352
5666.25651.0787
5671.9226-0.6042
5685.77030.82498
5691.6422-0.3343
5705.68240.68862
5715.16430.59096
5725.26190.90125
5733.41280.55761
5741.5342-0.61016
5753.40030.32923
5766.36580.96454
5775.54410.84785
5784.75360.76486
5792.9696-0.33306
5800.98172-0.742
5811.9475-0.19693
5822.8439-0.41598
5834.2464-0.11735
5844.2736-0.36149
5852.2056-1.3108
5861.2948-1.7201
587-0.024092-1.3777
5880.46569-1.4886
5892.2205-1.272
5905.85280.4868
591-0.40321-0.19275
592-0.7133-0.42461
5934.25460.28448
5945.3010.28636
595-1.5404-0.41063
5964.1430.39395
5975.00570.38945
5984.660.31697
5993.79360.87397
6004.73541.0822
6013.45930.79089
6024.66831.1432
6031.28021.7946
6041.61841.651
6051.54330.59839
6061.12740.74956
607-4.70270.19512
608-4.97840.59949
6090.22899-0.18024
6100.12942-0.016383
611-0.32844-0.37942
6121.2971-3.1384
613-1.9676-0.44326
614-1.6126-0.38802
615-0.62717-0.40315
616-1.49140.13281
617-0.91406-0.52596
618-0.41792-1.4367
619-1.3482-1.2811
620-0.49598-1.2795
621-0.32087-1.195
622-1.4332-1.1695
6230.52497-1.991
6242.1877-1.2846
6250.84818-1.9816
626-1.9108-2.318
6270.52334-2.0812
628-2.09620.49787
629-3.07820.49499
630-1.22640.47527
631-0.506520.37208
632-2.4107-0.0050762
633-2.22020.26455
634-3.2550.46787
635-3.79580.35632
636-1.96960.047406
6370.1604-0.59211
6382.2179-0.65352
639-2.46460.47143
640-4.09710.3452
641-3.37990.27342
642-3.7460.40116
643-3.16840.42415
644-0.6491-0.0069622
645-1.27040.081189
646-0.71367-0.23813
647-0.14075-0.2175
648-0.32476-0.53401
649-2.5172-0.073636
6500.27075-0.56872
651-1.7827-0.68874
652-0.82049-0.077733
653-0.58102-0.46309
6540.592850.067007
655-1.5139-0.16849
656-0.501560.016242
657-0.57634-0.05208
658-0.473130.28494
659-0.074246-0.62128
6601.5647-0.57342
6610.047226-0.48343
6620.19106-0.46254
6631.2911-0.52498
664-0.50575-0.9921
6651.0965-0.59277
6660.80136-0.93208
6671.0505-1.0278
6680.74786-0.73068
669-1.7605-0.25168
670-0.32022-0.5865
671-2.3797-0.056878
672-1.6331-0.24534
6736.124-0.32274
6745.8154-0.15118
6756.4498-0.085358
676-0.67115-0.50715
677-1.1832-0.60458
678-0.63327-0.6427
679-1.5115-0.52758
6800.5395-0.67498
6810.2926-0.98946
6820.97651-0.70435
683-0.83267-0.53295
684-1.5321-0.67873
685-2.1312-0.59895
686-1.125-0.44362
687-2.637-0.42023
688-1.5401-0.35561
689-1.7171-0.47147
690-1.538-0.27635
691-0.68441-0.544
6926.1996-0.26935
6937.34040.36609
6946.6544-0.0089732
6956.76580.15382
6966.72830.16974
6970.32274-0.59795
698-2.1756-0.11849
699-0.96951-0.058168
700-2.58140.053087
701-0.41618-0.26977
702-0.4254-0.55449
7030.24206-0.88604
7040.71874-0.81153
7050.42696-0.63951
706-1.9463-0.3416
707-3.5151-0.1576
708-2.5912-0.22377
709-2.5124-0.095936
710-2.8546-0.14203
711-2.5892-0.30957
712-0.90709-0.60579
7135.0982-0.56224
7145.3096-0.49954
7155.1924-0.21243
716-1.0740.07732
717-0.126770.38308
718-0.712110.43283
7190.19559-0.090339
7200.061586-0.12174
7210.53969-0.35954
7220.12867-0.80296
7230.50163-0.27705
7240.77296-0.61578
725-0.91818-0.24033
726-1.614-0.15326
727-1.2064-0.1862
728-1.7709-0.2704
729-1.8728-0.080131
730-0.192730.40923
731-0.774460.27441
732-0.32124-0.31934
733-0.469690.19213
7346.2276-0.040815
7355.9011-0.032841
7365.3598-0.051883
7376.2020.030063
738-0.949110.10275
739-0.38132-0.10487
740-2.04130.23419
741-1.46720.20742
742-0.93996-0.19616
743-1.8328-0.22151
744-1.7461-0.11247
745-0.86857-0.11353
746-2.4909-0.019532
747-1.334-0.21302
7480.78931-0.74406
7491.4785-0.57588
7500.3826-0.85482
751-1.01150.012446
752-1.63210.20094
753-1.14950.31051
754-1.03510.36847
7555.70620.045102
7565.1462-0.054099
7575.7481-0.088826
7584.3627-0.16823
7595.4016-0.093617
7600.298420.1434
7610.020244-0.064174
762-0.679860.12969
763-0.43540.14738
7640.90485-0.095677
765-1.4413-0.20693
766-0.96246-0.31527
767-1.5226-0.43802
768-0.390520.17845
769-1.1515-0.065315
7706.2690.11811
7715.2443-0.045846
7726.03650.33023
7735.78590.089774
7740.91781-0.46506
7750.36186-0.65151
7761.1295-0.25671
7771.2528-0.30134
7781.7444-0.87946
7791.1189-0.3363
7801.0643-0.25578
7812.5047-0.6677
7821.0652-0.53506
7831.3275-0.30173
7841.8757-0.48286
7851.7231-0.49213
7861.5788-0.276
7872.0791-0.2252
7881.6272-0.72777
7891.8367-0.24991
7901.5324-0.26286
7910.221630.019023
7921.0369-0.29083
7933.1347-0.4321
7942.488-0.6708
7952.952-0.2599
7962.5962-0.42964
7971.6188-0.6628
7982.0572-0.78708
7992.5396-0.6443
8003.5726-0.9347

PCA explained variance — how many dimensions?

Each bar reports the share of spectral variance explained by a component. Concentration in the first components indicates correlated wavelengths. This is not variance explained in the prediction target. This projection may use a different observation sample from the score plot.

PCA explained variance0%25%50%75%100%PC1: 94.0% (cumulative 94.0%)1PC2: 3.8% (cumulative 97.8%)2PC3: 1.5% (cumulative 99.3%)3PC4: 0.3% (cumulative 99.5%)4PC5: 0.2% (cumulative 99.8%)5PC6: 0.1% (cumulative 99.8%)6PC7: 0.0% (cumulative 99.9%)7PC8: 0.0% (cumulative 99.9%)8PC9: 0.0% (cumulative 99.9%)9PC10: 0.0% (cumulative 100.0%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
View explained variance values
Variance per displayed principal component
ComponentSpectral variance
PC194.00%
PC23.78%
PC31.48%
PC40.28%
PC50.22%
PC60.08%
PC70.05%
PC80.03%
PC90.02%
PC100.02%
X-Y spectral correlation 20

Pearson r measures the linear association between each spectral channel (X) and a numeric target (Y), from −1 to +1. The table reports peak and average absolute correlation and the share of channels with |r| ≥ 0.5. These are in-dataset associations, not validation scores or proof of causation.

Spectral association with LMA

Read Pearson correlation (−1 to +1) along the spectral axis (nm); the solid curve shows |r| and the dashed curve shows signed r.

X_transmittance · LMA spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale

Spectral association with LDMC

Read Pearson correlation (−1 to +1) along the spectral axis (nm); the solid curve shows |r| and the dashed curve shows signed r.

X_transmittance · LDMC spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale

Spectral association with EWT

Read Pearson correlation (−1 to +1) along the spectral axis (nm); the solid curve shows |r| and the dashed curve shows signed r.

X_transmittance · EWT spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation05001,0001,5002,0002,500|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
LMA0.7621,7140.66692.1%
LDMC0.2565300.1090.0%
EWT0.8681,3910.73288.4%
Cmass0.3685370.2290.0%
Nmass0.4237770.3090.0%
solubles_mass0.2477100.1230.0%
hemicellulose_mass0.1417070.02650.0%
cellulose_mass0.2447190.1780.0%
lignin_mass0.1926130.05620.0%
chlA_mass0.3452,2990.2610.0%
chlB_mass0.362,2990.2750.0%
car_mass0.3422,2960.2660.0%
Al_mass0.1226830.02220.0%
B208.9_mass0.1137910.07650.0%
B249.8_mass0.1187970.0770.0%
Ca_mass0.3837390.2650.0%
Cu_mass0.4172,2780.3160.0%
Fe_mass0.4272,2860.3370.0%
K_mass0.3194530.1660.0%
Mg_mass0.414540.3450.0%

Metric interpretation reference

Definitions, formulas and possible explanations for the reported values. A possible cause requires verification against acquisition records. Reading guide

Metric catalog 30

Look up each measured quantity, its calculation and the heuristic alert mapping before interpreting a high or low value.

FamilyMetricWhat it measuresHigher values suggestLower values suggestPossible causesCalculation / score
Data integrityInvalid/masked cell count (owner report)Null or masked cells in the evaluated populationTo investigateComplete according to the declared maskMissing data or validity mask; not evidence of an acquisition causeNative Preflight count of cells unavailable under x/null and valid_mask; denominator stays in native_metric.denominators.n_cells. Not legacy NaN ratio.
Data integrityNaN ratioMissing dataCorrupted spectrumFull spectrumAcquisition/export errorcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Data integrityInf countInfinite valuesCorruptionNormalInvalid calculationscount(isinf(X))alert = min(1, inf_count / 1)
Data integrityZero ratioNull columns or cellsTruncated spectrumNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Overall amplitudeMean reflectanceAverage levelToo light / background visibleToo darkBackground, geometrymean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Overall amplitudeArea under curveOverall intensityIllumination differenceNormalProbe distancetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Overall amplitudePeak-to-peak (PTP)Dynamic rangeStrong variabilityFlat spectrumSaturationmax(mean_spectrum) - min(mean_spectrum)alert increases when dynamic range is abnormally flat
Overall amplitudeVarianceSpectral variabilityNormal or heterogeneousFlat spectrumBad contactvar(X finite)alert increases when variance/dynamic range is abnormally flat
NoiseRoughness sigma proxyHigh frequency noiseNoisyStableLamp, detectormedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
NoiseRoughness S/N proxySignal qualityGood signalBad signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
NoiseBandwise roughness S/N proxyLocalized noiseReliable zoneProblem areaDetectormin(abs(mean_spectrum) / local second-derivative noise)alert decreases with worst-band SNR dB; >=35 dB is treated as low alert
Local artifactsSpike countNarrow peaksArtifactsClean spectrumCosmic rays, splicecount robust outliers in second derivativealert follows spike_rate, saturated at 1%
Local artifactsSpike ratePeak densitySuspicious spectrumNormalInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Local artifactsJump countDiscontinuitiesDetector connectionContinuousSplicecount robust outliers in first derivativealert follows jump_rate, saturated at 1%
Local artifactsJump rateJump frequencySpectral problemNormalCalibrationjump_count / (n_samples * (n_features - 1))alert = min(1, jump_rate / 0.01)
Local artifactsClip fractionSaturationClippingNormalDetector saturatedfraction of finite cells equal to repeated min/max extremaalert = min(1, clip_fraction / 0.01)
Spectral formBaseline slopeOverall slopeDriftStableIlluminationlinear slope of mean_spectrum over normalized axisalert = abs(slope / signal_scale), saturated at 0.5
Spectral formCurvature RMSCurvatureUnusual shapeSmoothBackground, splicemedian RMS(second derivative per spectrum)alert = curvature_rms / signal_scale, saturated at 1%
Spectral formD1 RMSLocal variabilityStructured spectrumFlatBiology or artifactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Multivariate outliersPCA Q (SPE)Not explained by PCAAtypical spectrumCompliantArtifact, mixturep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Multivariate outliersHotelling T²Extreme in PCAExtreme but consistentCentralNatural variabilityp95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Multivariate outliersMahalanobis HDistance to cloudGlobal outlierNormal populationDifferent domainp95(sqrt(T2)) / median(sqrt(T2))alert = min(1, mahalanobis_h_ratio / 4)
Comparison to average spectrumRMS to mean spectrumAverage distanceDifferent spectrumTypicalDomain shiftp95 RMS distance to dataset mean spectrumalert = RMS_p95 / signal_scale, saturated at 25%
Comparison to average spectrumSpectral Angle Mapper (SAM)Difference in shapeDifferent shapeSimilarBackground, geometryp95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RepeatabilityRMS intra-IDReproducibilityPoor repeatabilityStablePositioningmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RepeatabilitySAM intra-IDShape variationUnstableStableAcquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RepeatabilityCV intra-IDInternal variabilityBad controlStableOperatormedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure of the datasetPCA score densityClustersSubpopulationsHomogeneousDifferent batches1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure of the datasetkNN distance ratio (not LOF)Local anomalyIsolated spectrumNormal populationRare casesp95(mean kNN distance / median population mean kNN distance) in PCA-score space; not LOFalert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2)
Structure of the datasetIsolation Forest scoreGlobal anomalyAtypical spectrumNormalVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent
Technology-specific extensions

Find measurement-specific checks and acquisition context that can help interpret a source's spectral patterns.

TechnologyAdaptations / metricsTarget anomaliesPractical guidance
UV-Vis 300-1000 nmBaseline, overall slope, drift at edges 300-350 and 900-1000; metrics by zonesStray light, bad white, saturation, weak signal at the endsThe edges are often unstable; also calculate edge/middle scores.
UV-Vis 300-1000 nmSaturation / clipping near max absorbance or max reflectanceSignal clippedVery important if strong absorption.
UV-Vis 300-1000 nmRed-edge, peak position, band ratios for vegetationBiological shift or optical artifactHelps distinguish real change from acquisition problem.
UV-Vis 300-1000 nmSmoothness / roughness indexHigh frequency noiseOften more informative than the SNR alone.
MIR / ATR-FTIRATR contact quality index: overall intensity, total area, depth of key bandsPoor crystal-sample contactCrucial: many anomalies come from the ATR contact.
MIR / ATR-FTIRCO2 / H2O atmospheric bandsBad atmospheric correctionFrequent spurious peaks.
MIR / ATR-FTIRBaseline curvature / rubber-band residualDiffusion, contact, baseline driftVery useful before PCA.
MIR / ATR-FTIRPeak position shiftBad spectral alignment/calibrationImportant in FTIR because small shifts count.
MIR / ATR-FTIRBand area ratios on known bandsChemically incoherent spectrumTo be adapted by matrix: polysaccharides, proteins, lipids, etc.
HS-MSTotal Ion Current (TIC), Base Peak Intensity (BPI)Weak injection, unstable ionizationMS equivalent of the global spectral level.
HS-MSNumber of peaks detectedPoor or too noisy spectrumToo little = bad signal; too much = noise/contamination.
HS-MSMass accuracy / m/z driftMass calibration problemFundamental in HRMS.
HS-MSRetention time drift if LC/GC-MSChromatographic driftMonitor on standards/QC pools.
HS-MSBlank contamination scoreContaminants / carry-overCompare samples vs blanks.
HS-MSInternal standard CVInstrumental variabilityVery robust if standards available.
HS-MSMissingness by featureDetection instabilityCrucial for filtering variables.
With repetitionsIntra-sample RMSOverall repeatabilityApplicable to all technologies.
With repetitionsSAM / intra-sample correlationShape repeatabilityVery useful for spectra.
With repetitionsIntra-sample CV per band / featureLocal repeatabilityDetects unstable areas.
With repetitionsICC or variance componentsShare of sample vs. technical varianceVery useful if several repetitions per sample.
With repetitionsDistance to intra-ID centroidAberrant repetitionAllows you to flag the bad repetition rather than the entire sample.
Bug-hunting / supervised audits

Review suggested follow-up methods for suspected data issues and whether their results are available in this explorer.

Potential issue familySuggested methodsWhat it detectsExplorer availability
Global spectral shiftInter-dataset average spectrum correlation, DTW, cross-correlation, comparison of peak positionsWavelength shift, misalignment, different interpolationPartially calculated: cross-correlation lag and dispersion of peak positions vs. average spectrum.
Baseline / offset / gainRegression each spectrum vs average spectrum: x = a + b ref + residual; followed by a, b, residual RMSAdditive offset, multiplicative effect, baseline driftCalculated in reference.affine_*.
Row mixing / X-M-Y mismatchIndex check, row hash, ID duplication, intra-ID spectral distance, inconsistent labelsMixed up rows, misaligned metadata, Y assigned to wrong spectrumPartially covered by intra-ID repeatability; checks index/hash to add to the canonical pipeline.
Information leak / poorly split repetitionsGroupKFold by sample_id vs StratifiedKFold random; auditing partitions by sample_idArtificially good performance due to repetitionsRequires splits and benchmark model; not calculated by the descriptive card.
Label bugsClose samples in X but different Y, confident learning, systematic FP/FN errorsInverted Y, input errors, ambiguous classesRequires Y and/or model; recommended for supervised explorer.
Hidden subdomainsPCA/UMAP/t-SNE + unsupervised clustering + association with dataset/Y/date/operatorBatches, campaigns, probes, backgrounds not providedPartially calculated by PCA and distance ratio kNN (not LOF); UMAP/t-SNE outside the static card.
Unknown localized artifactsWavelength x dataset map: mean difference, variance difference, KS per wavelengthUnanticipated anomalous spectral regionsTo be calculated at the bank level when several datasets share a spectral axis.
Instrumental breaksDiscontinuities in derivatives, changepoint detectionSplice, detector connection, local jump not providedCalculated by jump/spike rates; more advanced changepoint to add.
Spectral mixing/contaminationNMF / unmixing / reconstruction by convex hullExternal component: background, plastic, soilNot calculated automatically; requires component assumptions or large library.
Unstable but predictive featuresModel importance vs. QC instability by variableModel that learns an artifact rather than a biological signalRequires supervised model; recommended for benchmark reporting.

Curated scientific variables

Scientific roles derived from the source contract. M denotes experimental metadata; Y denotes informative response variables. Reading guide

7 experimental metadata fields (M) · 49 informative targets (Y).

VariableRoleDistinct valuesCompleteRange / balance
siteM47100%IR 260
latitudeM1,728100%-34.81 – 48.81
longitudeM1,727100%-123.7 – 116.1
dateM130100%IR 37
measurement_dateM130100%IR 37
projectM11100%IR 43.6
stageM8100%IR 237.9
species__speciesY106100%IR 120
genusY66100%IR 88.33
species__latin_speciesY93100%IR 120
growth_formY4100%IR 70.25
familyY31100%IR 89.33
functional_groupY7100%IR 142.3
lmaY1,943100%0.008442 – 0.4077
ldmcY1,930100%35.81 – 573
ewtY1,929100%0.03229 – 0.5179
cmassY884100%36.72 – 56.95
nmassY1,892100%0.7948 – 5.953
solubles_massY1,919100%23.68 – 88.95
hemicellulose_massY1,915100%2.229 – 42.93
cellulose_massY1,946100%5.19 – 34.32
lignin_massY1,946100%0.5314 – 23.44
chla_massY1,855100%1.242 – 28.57
chlb_massY1,717100%0.388 – 10.82
car_massY1,559100%0.193 – 5.297
al_massY199100%0 – 0.332
b208_9_massY286100%-0.29 – 0.43
b249_8_massY274100%-0.26 – 0.4
ca_massY653100%0.959 – 36.54
cu_massY90100%0 – 0.027
fe_massY188100%0.01497 – 0.245
k_massY636100%1.058 – 27.05
mg_massY577100%0.482 – 7.862
mn_massY372100%0 – 1.398
na_massY500100%0 – 4.872
p_massY522100%0.2228 – 7.178
zn_massY241100%0.001424 – 0.37
nareaY1,93750%3.194e-05 – 0.0005152
careaY1,93750%0.0003681 – 0.02103
solubles_areaY1,89350%0.0005307 – 0.02528
hemicellulose_areaY1,88950%7.847e-05 – 0.005191
cellulose_areaY1,92050%0.00012 – 0.007309
lignin_areaY1,92050%2.12e-05 – 0.004556
chla_areaY1,91550%8.885e-06 – 0.0002939
chlb_areaY1,91550%2.971e-06 – 9.463e-05
car_areaY1,91550%2.482e-06 – 5.86e-05
al_areaY64250%0 – 4.327e-06
ca_areaY66550%1.26e-05 – 0.0003779
cu_areaY64050%0 – 2.611e-07
fe_areaY66450%1.799e-07 – 2.787e-06
k_areaY66550%1.482e-05 – 0.0002228
mg_areaY66550%3.179e-06 – 8.179e-05
mn_areaY66450%0 – 1.62e-05
na_areaY63350%0 – 6.958e-05
p_areaY66550%3.089e-06 – 7.277e-05
zn_areaY66450%2.297e-08 – 2.89e-06

Identifiers and sampling groups remain available separately. Statistics count exported observations.

Variables

Declared prediction targets and recorded metadata, with distributions and missing-value counts. Identifiers are not automatically prediction targets. Reading guide

Targets 51

species

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

species classesPopulus tremuloides MichauxPopulus tremuloides Michaux: 240240Betula populifolia MarshallBetula populifolia Marshall: 208208Acer rubrum LinnaeusAcer rubrum Linnaeus: 180180Acer saccharum MarshallAcer saccharum Marshall: 162162Phragmites australis (Cavanil…Phragmites australis (Cavanilles) Trinius ex Steudel subsp. australis: 156156Solidago altissima LinnaeusSolidago altissima Linnaeus: 150150Phalaris arundinacea LinnaeusPhalaris arundinacea Linnaeus: 150150Agonis flexuosa (Willd.) SweetAgonis flexuosa (Willd.) Sweet: 136136Bromus inermis LeysserBromus inermis Leysser: 120120Typha latifolia LinnaeusTypha latifolia Linnaeus: 120120+10 more+10 more: 576576
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
106
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.9
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
120
Top class
?Most frequent recorded category and its observation count.
Populus tremuloides Michaux (240)

latin.genus

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

latin.genus classesAcerAcer: 530530PopulusPopulus: 366366BetulaBetula: 318318SolidagoSolidago: 186186PhragmitesPhragmites: 156156BromusBromus: 152152QuercusQuercus: 150150PhalarisPhalaris: 150150TyphaTypha: 146146AgonisAgonis: 136136+10 more+10 more: 628628
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
66
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.85
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
9e+01
Top class
?Most frequent recorded category and its observation count.
Acer (530)

latin.species

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

latin.species classestremuloidestremuloides: 240240populifoliapopulifolia: 208208rubrumrubrum: 180180saccharumsaccharum: 162162australisaustralis: 156156altissimaaltissima: 154154arundinaceaarundinacea: 150150flexuosaflexuosa: 136136inermisinermis: 120120latifolialatifolia: 120120+10 more+10 more: 672672
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
93
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.91
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
120
Top class
?Most frequent recorded category and its observation count.
tremuloides (240)

plant.id

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

plant.id classes85543258554325: 141489851848985184: 121289854718985471: 121289855998985599: 121289855348985534: 121289854318985431: 121289856558985655: 121289851908985190: 121289850088985008: 121289852898985289: 1212+10 more+10 more: 120120
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2
Classes
?Number of distinct recorded category values.
1,738
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.99
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
7
Top class
?Most frequent recorded category and its observation count.
8554325 (14)

growth.form

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

growth.form classestreetree: 2,2482,248herbherb: 1,2161,216shrubshrub: 446446vinevine: 3232
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
4
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.7
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
7e+01
Top class
?Most frequent recorded category and its observation count.
tree (2,248)

family

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

family classesSapindaceaeSapindaceae: 536536PoaceaePoaceae: 526526SalicaceaeSalicaceae: 396396BetulaceaeBetulaceae: 386386FagaceaeFagaceae: 244244PinaceaePinaceae: 228228AsteraceaeAsteraceae: 222222RosaceaeRosaceae: 198198TyphaceaeTyphaceae: 146146EricaceaeEricaceae: 144144+10 more+10 more: 664664
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
31
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.84
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
9e+01
Top class
?Most frequent recorded category and its observation count.
Sapindaceae (536)

genus

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

genus classesAcerAcer: 530530PopulusPopulus: 366366BetulaBetula: 318318SolidagoSolidago: 186186PhragmitesPhragmites: 156156BromusBromus: 152152QuercusQuercus: 150150PhalarisPhalaris: 150150TyphaTypha: 146146AgonisAgonis: 136136+10 more+10 more: 628628
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
66
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.85
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
9e+01
Top class
?Most frequent recorded category and its observation count.
Acer (530)

functional.group

target · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

functional.group classesbroadleafbroadleaf: 1,9921,992graminoidgraminoid: 718718forbforb: 484484shrubshrub: 446446coniferconifer: 256256vinevine: 3232fernfern: 1414
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
7
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.72
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
1e+02
Top class
?Most frequent recorded category and its observation count.
broadleaf (1,992)

LMA

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

LMA distribution05001,0001,5000.008442 – 0.02508: 760.02508 – 0.04171: 4840.04171 – 0.05835: 10400.05835 – 0.07499: 10800.07499 – 0.09162: 4860.09162 – 0.1083: 1400.1083 – 0.1249: 1240.1249 – 0.1415: 700.1415 – 0.1582: 720.1582 – 0.1748: 580.1748 – 0.1914: 640.1914 – 0.2081: 420.2081 – 0.2247: 280.2247 – 0.2414: 300.2414 – 0.258: 120.258 – 0.2746: 100.2746 – 0.2913: 60.2913 – 0.3079: 160.3079 – 0.3245: 180.3245 – 0.3412: 60.3412 – 0.3578: 60.3578 – 0.3744: 40.3744 – 0.3911: 120.3911 – 0.4077: 20.00.10.20.30.40.5
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 56
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.07772 ± 0.0539
Median
?50th percentile: half the non-missing values lie at or below it.
0.06318
Range
?Smallest and largest recorded non-missing values.
0.008442 – 0.4077
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.694
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.8 / 9.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

LDMC

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

LDMC distribution020040060035.81 – 58.19: 2458.19 – 80.57: 1680.57 – 102.9: 0102.9 – 125.3: 12125.3 – 147.7: 46147.7 – 170.1: 82170.1 – 192.5: 98192.5 – 214.9: 98214.9 – 237.2: 116237.2 – 259.6: 132259.6 – 282: 138282 – 304.4: 220304.4 – 326.8: 252326.8 – 349.1: 334349.1 – 371.5: 384371.5 – 393.9: 456393.9 – 416.3: 442416.3 – 438.7: 392438.7 – 461.1: 292461.1 – 483.4: 136483.4 – 505.8: 126505.8 – 528.2: 38528.2 – 550.6: 20550.6 – 573: 60200400600
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 82
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
353.7 ± 92.4
Median
?50th percentile: half the non-missing values lie at or below it.
370.8
Range
?Smallest and largest recorded non-missing values.
35.81 – 573
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.261
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.75 / 0.4
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

EWT

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

EWT distribution05001,0001,5000.03229 – 0.05252: 840.05252 – 0.07276: 4980.07276 – 0.09299: 10880.09299 – 0.1132: 8140.1132 – 0.1335: 3680.1335 – 0.1537: 3260.1537 – 0.1739: 1440.1739 – 0.1942: 880.1942 – 0.2144: 680.2144 – 0.2346: 560.2346 – 0.2549: 400.2549 – 0.2751: 160.2751 – 0.2953: 280.2953 – 0.3156: 300.3156 – 0.3358: 280.3358 – 0.356: 360.356 – 0.3763: 420.3763 – 0.3965: 400.3965 – 0.4167: 200.4167 – 0.437: 140.437 – 0.4572: 220.4572 – 0.4774: 00.4774 – 0.4977: 20.4977 – 0.5179: 60.00.20.40.6
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 84
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.1241 ± 0.0778
Median
?50th percentile: half the non-missing values lie at or below it.
0.09779
Range
?Smallest and largest recorded non-missing values.
0.03229 – 0.5179
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.627
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.4 / 5.7
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Cmass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Cmass distribution020040060036.72 – 37.56: 237.56 – 38.41: 838.41 – 39.25: 439.25 – 40.09: 1640.09 – 40.93: 1040.93 – 41.78: 6841.78 – 42.62: 8042.62 – 43.46: 17243.46 – 44.31: 24644.31 – 45.15: 48045.15 – 45.99: 49045.99 – 46.84: 35046.84 – 47.68: 39647.68 – 48.52: 47648.52 – 49.36: 42649.36 – 50.21: 27050.21 – 51.05: 16051.05 – 51.89: 12251.89 – 52.74: 10252.74 – 53.58: 3653.58 – 54.42: 854.42 – 55.26: 055.26 – 56.11: 256.11 – 56.95: 2102050100
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 16
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
46.92 ± 2.71
Median
?50th percentile: half the non-missing values lie at or below it.
46.92
Range
?Smallest and largest recorded non-missing values.
36.72 – 56.95
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.0577
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.0034 / -0.055
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
yes

Nmass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Nmass distribution02004006000.7948 – 1.01: 781.01 – 1.225: 2141.225 – 1.44: 2361.44 – 1.655: 2441.655 – 1.869: 3221.869 – 2.084: 4742.084 – 2.299: 5562.299 – 2.514: 5062.514 – 2.729: 4742.729 – 2.944: 2882.944 – 3.159: 1923.159 – 3.374: 1163.374 – 3.589: 743.589 – 3.804: 543.804 – 4.019: 384.019 – 4.234: 104.234 – 4.449: 164.449 – 4.663: 84.663 – 4.878: 64.878 – 5.093: 65.093 – 5.308: 25.308 – 5.523: 45.523 – 5.738: 45.738 – 5.953: 40246
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 16
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
2.257 ± 0.709
Median
?50th percentile: half the non-missing values lie at or below it.
2.234
Range
?Smallest and largest recorded non-missing values.
0.7948 – 5.953
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.314
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.71 / 1.8
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

solubles_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

solubles_mass distribution020040060023.68 – 26.4: 226.4 – 29.12: 429.12 – 31.84: 231.84 – 34.56: 1234.56 – 37.28: 7837.28 – 40: 12840 – 42.72: 14442.72 – 45.44: 13445.44 – 48.16: 14848.16 – 50.88: 10650.88 – 53.6: 11253.6 – 56.31: 13056.31 – 59.03: 18059.03 – 61.75: 19661.75 – 64.47: 25264.47 – 67.19: 28267.19 – 69.91: 37469.91 – 72.63: 43872.63 – 75.35: 40875.35 – 78.07: 32078.07 – 80.79: 23080.79 – 83.51: 9883.51 – 86.23: 4486.23 – 88.95: 16102050100
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 104
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
63.9 ± 12.8
Median
?50th percentile: half the non-missing values lie at or below it.
67.26
Range
?Smallest and largest recorded non-missing values.
23.68 – 88.95
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.201
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.64 / -0.57
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

hemicellulose_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

hemicellulose_mass distribution02505007502.229 – 3.925: 243.925 – 5.621: 925.621 – 7.317: 4287.317 – 9.012: 6729.012 – 10.71: 56210.71 – 12.4: 46212.4 – 14.1: 28014.1 – 15.8: 18015.8 – 17.49: 12017.49 – 19.19: 12419.19 – 20.88: 7020.88 – 22.58: 10422.58 – 24.27: 9224.27 – 25.97: 14025.97 – 27.67: 11627.67 – 29.36: 9429.36 – 31.06: 7831.06 – 32.75: 8632.75 – 34.45: 6034.45 – 36.14: 2836.14 – 37.84: 237.84 – 39.54: 1039.54 – 41.23: 441.23 – 42.93: 20204060
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 112
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
14.15 ± 7.95
Median
?50th percentile: half the non-missing values lie at or below it.
11.07
Range
?Smallest and largest recorded non-missing values.
2.229 – 42.93
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.562
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.1 / 0.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

cellulose_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

cellulose_mass distribution02004006005.19 – 6.404: 606.404 – 7.618: 3087.618 – 8.831: 4608.831 – 10.04: 52610.04 – 11.26: 48811.26 – 12.47: 39412.47 – 13.69: 29613.69 – 14.9: 21214.9 – 16.11: 12816.11 – 17.33: 11217.33 – 18.54: 9818.54 – 19.75: 3819.75 – 20.97: 3220.97 – 22.18: 2822.18 – 23.39: 8023.39 – 24.61: 11824.61 – 25.82: 15425.82 – 27.04: 13627.04 – 28.25: 8828.25 – 29.46: 6029.46 – 30.68: 3630.68 – 31.89: 3231.89 – 33.1: 633.1 – 34.32: 2010203040
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 50
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
13.95 ± 6.58
Median
?50th percentile: half the non-missing values lie at or below it.
11.54
Range
?Smallest and largest recorded non-missing values.
5.19 – 34.32
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.472
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.1 / -0.022
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

lignin_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

lignin_mass distribution02004000.5314 – 1.486: 1381.486 – 2.44: 3902.44 – 3.395: 2303.395 – 4.349: 1944.349 – 5.303: 2805.303 – 6.258: 3126.258 – 7.212: 3307.212 – 8.167: 3368.167 – 9.121: 2989.121 – 10.08: 29810.08 – 11.03: 27211.03 – 11.98: 18211.98 – 12.94: 15612.94 – 13.89: 14213.89 – 14.85: 11014.85 – 15.8: 8215.8 – 16.76: 4816.76 – 17.71: 3417.71 – 18.67: 2618.67 – 19.62: 1419.62 – 20.57: 1020.57 – 21.53: 421.53 – 22.48: 422.48 – 23.44: 20102030
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 50
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
7.68 ± 4.24
Median
?50th percentile: half the non-missing values lie at or below it.
7.372
Range
?Smallest and largest recorded non-missing values.
0.5314 – 23.44
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.552
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.45 / -0.25
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

chlA_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

chlA_mass distribution02505007501.242 – 2.381: 2302.381 – 3.519: 3463.519 – 4.658: 3324.658 – 5.796: 4965.796 – 6.935: 6226.935 – 8.073: 5288.073 – 9.212: 4329.212 – 10.35: 26410.35 – 11.49: 18611.49 – 12.63: 13212.63 – 13.77: 10613.77 – 14.9: 6414.9 – 16.04: 5016.04 – 17.18: 2217.18 – 18.32: 2218.32 – 19.46: 1619.46 – 20.6: 420.6 – 21.74: 621.74 – 22.87: 422.87 – 24.01: 624.01 – 25.15: 425.15 – 26.29: 226.29 – 27.43: 227.43 – 28.57: 60102030
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 60
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
7.26 ± 3.7
Median
?50th percentile: half the non-missing values lie at or below it.
6.811
Range
?Smallest and largest recorded non-missing values.
1.242 – 28.57
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.509
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.3 / 3.3
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

chlB_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

chlB_mass distribution02505007500.388 – 0.8227: 2420.8227 – 1.257: 4001.257 – 1.692: 4381.692 – 2.127: 6622.127 – 2.562: 6682.562 – 2.996: 4882.996 – 3.431: 3403.431 – 3.866: 2063.866 – 4.301: 1344.301 – 4.735: 1104.735 – 5.17: 705.17 – 5.605: 445.605 – 6.04: 266.04 – 6.474: 86.474 – 6.909: 146.909 – 7.344: 87.344 – 7.779: 47.779 – 8.213: 48.213 – 8.648: 68.648 – 9.083: 29.083 – 9.518: 09.518 – 9.952: 09.952 – 10.39: 410.39 – 10.82: 4051015
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 60
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
2.434 ± 1.27
Median
?50th percentile: half the non-missing values lie at or below it.
2.259
Range
?Smallest and largest recorded non-missing values.
0.388 – 10.82
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.522
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.5 / 4.9
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

car_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

car_mass distribution02505007500.193 – 0.4057: 920.4057 – 0.6183: 2600.6183 – 0.831: 1880.831 – 1.044: 2861.044 – 1.256: 4981.256 – 1.469: 6221.469 – 1.682: 5461.682 – 1.894: 4041.894 – 2.107: 2902.107 – 2.32: 1902.32 – 2.532: 1562.532 – 2.745: 1162.745 – 2.957: 722.957 – 3.17: 403.17 – 3.383: 363.383 – 3.595: 383.595 – 3.808: 123.808 – 4.021: 104.021 – 4.233: 84.233 – 4.446: 24.446 – 4.659: 44.659 – 4.871: 44.871 – 5.084: 45.084 – 5.297: 40246
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 60
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.554 ± 0.715
Median
?50th percentile: half the non-missing values lie at or below it.
1.464
Range
?Smallest and largest recorded non-missing values.
0.193 – 5.297
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.46
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.99 / 2.1
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Al_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Al_mass distribution02004000 – 0.01383: 1460.01383 – 0.02767: 2520.02767 – 0.0415: 3060.0415 – 0.05533: 2180.05533 – 0.06917: 1300.06917 – 0.083: 1300.083 – 0.09683: 520.09683 – 0.1107: 480.1107 – 0.1245: 160.1245 – 0.1383: 60.1383 – 0.1522: 60.1522 – 0.166: 120.166 – 0.1798: 60.1798 – 0.1937: 120.1937 – 0.2075: 60.2075 – 0.2213: 20.2213 – 0.2352: 20.2352 – 0.249: 00.249 – 0.2628: 00.2628 – 0.2767: 00.2767 – 0.2905: 00.2905 – 0.3043: 20.3043 – 0.3182: 00.3182 – 0.332: 20.00.10.20.30.4
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,588
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.04917 ± 0.039
Median
?50th percentile: half the non-missing values lie at or below it.
0.04
Range
?Smallest and largest recorded non-missing values.
0 – 0.332
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.794
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.3 / 8.9
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

B208.9_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

B208.9_mass distribution0100200-0.29 – -0.26: 2-0.26 – -0.23: 38-0.23 – -0.2: 18-0.2 – -0.17: 34-0.17 – -0.14: 38-0.14 – -0.11: 16-0.11 – -0.08: 34-0.08 – -0.05: 48-0.05 – -0.02: 60-0.02 – 0.01: 1440.01 – 0.04: 1380.04 – 0.07: 1820.07 – 0.1: 1440.1 – 0.13: 1020.13 – 0.16: 580.16 – 0.19: 300.19 – 0.22: 340.22 – 0.25: 260.25 – 0.28: 100.28 – 0.31: 180.31 – 0.34: 260.34 – 0.37: 80.37 – 0.4: 80.4 – 0.43: 4-0.4-0.20.00.20.40.6
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,722
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.04166 ± 0.127
Median
?50th percentile: half the non-missing values lie at or below it.
0.045
Range
?Smallest and largest recorded non-missing values.
-0.29 – 0.43
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
3.04
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.02 / 0.57
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

B249.8_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

B249.8_mass distribution0100200-0.26 – -0.2325: 6-0.2325 – -0.205: 36-0.205 – -0.1775: 24-0.1775 – -0.15: 32-0.15 – -0.1225: 32-0.1225 – -0.095: 16-0.095 – -0.0675: 38-0.0675 – -0.04: 44-0.04 – -0.0125: 68-0.0125 – 0.015: 1440.015 – 0.0425: 1500.0425 – 0.07: 1760.07 – 0.0975: 1220.0975 – 0.125: 1220.125 – 0.1525: 480.1525 – 0.18: 280.18 – 0.2075: 340.2075 – 0.235: 280.235 – 0.2625: 120.2625 – 0.29: 260.29 – 0.3175: 140.3175 – 0.345: 120.345 – 0.3725: 40.3725 – 0.4: 4-0.4-0.20.00.20.4
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,722
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.04184 ± 0.117
Median
?50th percentile: half the non-missing values lie at or below it.
0.045
Range
?Smallest and largest recorded non-missing values.
-0.26 – 0.4
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
2.8
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.0061 / 0.52
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Ca_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Ca_mass distribution01002000.959 – 2.441: 462.441 – 3.924: 1043.924 – 5.406: 1525.406 – 6.889: 1626.889 – 8.371: 1888.371 – 9.854: 1309.854 – 11.34: 15411.34 – 12.82: 8612.82 – 14.3: 7614.3 – 15.78: 5815.78 – 17.27: 4417.27 – 18.75: 3418.75 – 20.23: 3620.23 – 21.71: 2621.71 – 23.2: 1023.2 – 24.68: 1224.68 – 26.16: 1026.16 – 27.64: 027.64 – 29.13: 429.13 – 30.61: 830.61 – 32.09: 832.09 – 33.57: 633.57 – 35.06: 035.06 – 36.54: 2010203040
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,586
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
9.988 ± 5.97
Median
?50th percentile: half the non-missing values lie at or below it.
8.58
Range
?Smallest and largest recorded non-missing values.
0.959 – 36.54
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.597
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.3 / 2.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Cu_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Cu_mass distribution02004006000 – 0.001125: 1000.001125 – 0.00225: 840.00225 – 0.003375: 700.003375 – 0.0045: 1400.0045 – 0.005625: 1400.005625 – 0.00675: 1420.00675 – 0.007875: 1060.007875 – 0.009: 980.009 – 0.01012: 4120.01012 – 0.01125: 260.01125 – 0.01237: 80.01237 – 0.0135: 20.0135 – 0.01462: 40.01462 – 0.01575: 00.01575 – 0.01687: 20.01687 – 0.018: 20.018 – 0.01912: 20.01912 – 0.02025: 20.02025 – 0.02137: 40.02137 – 0.0225: 20.0225 – 0.02362: 00.02362 – 0.02475: 20.02475 – 0.02587: 00.02587 – 0.027: 20.000.010.020.03
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,592
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.006616 ± 0.00361
Median
?50th percentile: half the non-missing values lie at or below it.
0.006
Range
?Smallest and largest recorded non-missing values.
0 – 0.027
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.546
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.6 / 2.4
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Fe_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Fe_mass distribution01002000.01497 – 0.02455: 680.02455 – 0.03414: 1520.03414 – 0.04372: 1340.04372 – 0.05331: 1800.05331 – 0.06289: 1960.06289 – 0.07248: 1840.07248 – 0.08206: 1240.08206 – 0.09165: 920.09165 – 0.1012: 660.1012 – 0.1108: 260.1108 – 0.1204: 380.1204 – 0.13: 60.13 – 0.1396: 240.1396 – 0.1492: 140.1492 – 0.1587: 220.1587 – 0.1683: 60.1683 – 0.1779: 20.1779 – 0.1875: 20.1875 – 0.1971: 40.1971 – 0.2067: 40.2067 – 0.2162: 40.2162 – 0.2258: 40.2258 – 0.2354: 00.2354 – 0.245: 20.00.10.20.3
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,588
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.06682 ± 0.0347
Median
?50th percentile: half the non-missing values lie at or below it.
0.06
Range
?Smallest and largest recorded non-missing values.
0.01497 – 0.245
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.52
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.5 / 3.5
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

K_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

K_mass distribution01002003001.058 – 2.141: 402.141 – 3.224: 1263.224 – 4.307: 1684.307 – 5.389: 2725.389 – 6.472: 2506.472 – 7.555: 2007.555 – 8.638: 1148.638 – 9.72: 629.72 – 10.8: 5810.8 – 11.89: 1411.89 – 12.97: 612.97 – 14.05: 614.05 – 15.13: 615.13 – 16.22: 616.22 – 17.3: 617.3 – 18.38: 818.38 – 19.47: 619.47 – 20.55: 420.55 – 21.63: 021.63 – 22.71: 022.71 – 23.8: 223.8 – 24.88: 024.88 – 25.96: 025.96 – 27.05: 20102030
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,586
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
6.155 ± 3.06
Median
?50th percentile: half the non-missing values lie at or below it.
5.737
Range
?Smallest and largest recorded non-missing values.
1.058 – 27.05
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.497
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.1 / 7.6
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Mg_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Mg_mass distribution01002000.482 – 0.7895: 760.7895 – 1.097: 1241.097 – 1.405: 701.405 – 1.712: 1261.712 – 2.019: 1902.019 – 2.327: 1942.327 – 2.635: 1962.635 – 2.942: 1362.942 – 3.25: 1003.25 – 3.557: 523.557 – 3.864: 443.864 – 4.172: 164.172 – 4.479: 64.479 – 4.787: 64.787 – 5.095: 105.095 – 5.402: 05.402 – 5.71: 25.71 – 6.017: 06.017 – 6.325: 26.325 – 6.632: 06.632 – 6.939: 26.939 – 7.247: 07.247 – 7.554: 07.554 – 7.862: 402468
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,586
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
2.193 ± 0.95
Median
?50th percentile: half the non-missing values lie at or below it.
2.143
Range
?Smallest and largest recorded non-missing values.
0.482 – 7.862
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.433
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.1 / 4.1
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Mn_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Mn_mass distribution02004000 – 0.05825: 3800.05825 – 0.1165: 3140.1165 – 0.1747: 1540.1747 – 0.233: 980.233 – 0.2913: 740.2913 – 0.3495: 740.3495 – 0.4077: 500.4077 – 0.466: 520.466 – 0.5242: 400.5242 – 0.5825: 280.5825 – 0.6407: 200.6407 – 0.699: 160.699 – 0.7572: 120.7572 – 0.8155: 100.8155 – 0.8737: 80.8737 – 0.932: 80.932 – 0.9902: 60.9902 – 1.048: 21.048 – 1.107: 61.107 – 1.165: 01.165 – 1.223: 01.223 – 1.281: 21.281 – 1.34: 01.34 – 1.398: 20.00.51.01.5
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,586
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.2016 ± 0.217
Median
?50th percentile: half the non-missing values lie at or below it.
0.11
Range
?Smallest and largest recorded non-missing values.
0 – 1.398
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.08
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.9 / 4.1
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Na_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Na_mass distribution01002003000 – 0.203: 1860.203 – 0.406: 1300.406 – 0.609: 2080.609 – 0.812: 2860.812 – 1.015: 2421.015 – 1.218: 1221.218 – 1.421: 481.421 – 1.624: 241.624 – 1.827: 281.827 – 2.03: 202.03 – 2.233: 42.233 – 2.436: 202.436 – 2.639: 62.639 – 2.842: 102.842 – 3.045: 63.045 – 3.248: 43.248 – 3.451: 03.451 – 3.654: 03.654 – 3.857: 63.857 – 4.06: 24.06 – 4.263: 24.263 – 4.466: 04.466 – 4.669: 04.669 – 4.872: 20246
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,586
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.7995 ± 0.625
Median
?50th percentile: half the non-missing values lie at or below it.
0.72
Range
?Smallest and largest recorded non-missing values.
0 – 4.872
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.782
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.1 / 7.4
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

P_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

P_mass distribution02004000.2228 – 0.5126: 420.5126 – 0.8024: 1060.8024 – 1.092: 1841.092 – 1.382: 3981.382 – 1.672: 2921.672 – 1.962: 1261.962 – 2.251: 482.251 – 2.541: 362.541 – 2.831: 202.831 – 3.121: 203.121 – 3.411: 123.411 – 3.7: 183.7 – 3.99: 103.99 – 4.28: 124.28 – 4.57: 24.57 – 4.86: 64.86 – 5.149: 45.149 – 5.439: 25.439 – 5.729: 65.729 – 6.019: 46.019 – 6.309: 26.309 – 6.598: 26.598 – 6.888: 06.888 – 7.178: 402468
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,586
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.553 ± 0.914
Median
?50th percentile: half the non-missing values lie at or below it.
1.354
Range
?Smallest and largest recorded non-missing values.
0.2228 – 7.178
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.589
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.7 / 9.8
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Zn_mass

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Zn_mass distribution02004006000.001424 – 0.01678: 4520.01678 – 0.03214: 3020.03214 – 0.0475: 500.0475 – 0.06285: 300.06285 – 0.07821: 560.07821 – 0.09357: 600.09357 – 0.1089: 640.1089 – 0.1243: 940.1243 – 0.1396: 360.1396 – 0.155: 520.155 – 0.1704: 340.1704 – 0.1857: 280.1857 – 0.2011: 260.2011 – 0.2164: 120.2164 – 0.2318: 140.2318 – 0.2471: 120.2471 – 0.2625: 60.2625 – 0.2779: 40.2779 – 0.2932: 120.2932 – 0.3086: 20.3086 – 0.3239: 20.3239 – 0.3393: 20.3393 – 0.3546: 20.3546 – 0.37: 20.00.10.20.30.4
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,588
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.06444 ± 0.07
Median
?50th percentile: half the non-missing values lie at or below it.
0.029
Range
?Smallest and largest recorded non-missing values.
0.001424 – 0.37
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.09
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.4 / 1.6
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Narea

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Narea distribution02004003.194e-05 – 5.207e-05: 255.207e-05 – 7.221e-05: 507.221e-05 – 9.234e-05: 1569.234e-05 – 0.0001125: 3110.0001125 – 0.0001326: 2700.0001326 – 0.0001527: 2790.0001527 – 0.0001729: 2410.0001729 – 0.000193: 1640.000193 – 0.0002132: 1330.0002132 – 0.0002333: 1030.0002333 – 0.0002534: 760.0002534 – 0.0002736: 380.0002736 – 0.0002937: 420.0002937 – 0.0003138: 160.0003138 – 0.000334: 80.000334 – 0.0003541: 50.0003541 – 0.0003742: 50.0003742 – 0.0003944: 30.0003944 – 0.0004145: 50.0004145 – 0.0004346: 50.0004346 – 0.0004548: 00.0004548 – 0.0004749: 00.0004749 – 0.0004951: 00.0004951 – 0.0005152: 20.00000.00020.00040.0006
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,005
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.0001542 ± 6.17e-05
Median
?50th percentile: half the non-missing values lie at or below it.
0.0001436
Range
?Smallest and largest recorded non-missing values.
3.194e-05 – 0.0005152
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.4
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.2 / 2.5
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Carea

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Carea distribution02004006000.0003681 – 0.001229: 470.001229 – 0.00209: 3690.00209 – 0.002951: 5430.002951 – 0.003812: 4930.003812 – 0.004673: 1650.004673 – 0.005534: 570.005534 – 0.006394: 460.006394 – 0.007255: 310.007255 – 0.008116: 280.008116 – 0.008977: 310.008977 – 0.009838: 320.009838 – 0.0107: 260.0107 – 0.01156: 200.01156 – 0.01242: 80.01242 – 0.01328: 40.01328 – 0.01414: 30.01414 – 0.015: 40.015 – 0.01586: 90.01586 – 0.01673: 70.01673 – 0.01759: 20.01759 – 0.01845: 40.01845 – 0.01931: 30.01931 – 0.02017: 40.02017 – 0.02103: 10.000.010.020.03
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,005
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.003718 ± 0.00278
Median
?50th percentile: half the non-missing values lie at or below it.
0.002963
Range
?Smallest and largest recorded non-missing values.
0.0003681 – 0.02103
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.746
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.8 / 9.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

solubles_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

solubles_area distribution02004006000.0005307 – 0.001562: 550.001562 – 0.002593: 3080.002593 – 0.003624: 3710.003624 – 0.004655: 4240.004655 – 0.005686: 3350.005686 – 0.006717: 1190.006717 – 0.007748: 520.007748 – 0.008779: 290.008779 – 0.00981: 240.00981 – 0.01084: 230.01084 – 0.01187: 180.01187 – 0.0129: 300.0129 – 0.01393: 270.01393 – 0.01497: 190.01497 – 0.016: 150.016 – 0.01703: 110.01703 – 0.01806: 90.01806 – 0.01909: 20.01909 – 0.02012: 100.02012 – 0.02115: 30.02115 – 0.02218: 10.02218 – 0.02321: 20.02321 – 0.02425: 50.02425 – 0.02528: 10.000.010.020.03
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,049
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.004988 ± 0.00354
Median
?50th percentile: half the non-missing values lie at or below it.
0.004166
Range
?Smallest and largest recorded non-missing values.
0.0005307 – 0.02528
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.71
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.4 / 6.7
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

hemicellulose_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

hemicellulose_area distribution02004006007.847e-05 – 0.0002915: 840.0002915 – 0.0005045: 3580.0005045 – 0.0007175: 4600.0007175 – 0.0009305: 2780.0009305 – 0.001144: 1690.001144 – 0.001357: 1310.001357 – 0.00157: 820.00157 – 0.001783: 540.001783 – 0.001996: 340.001996 – 0.002209: 350.002209 – 0.002422: 390.002422 – 0.002635: 290.002635 – 0.002848: 290.002848 – 0.003061: 330.003061 – 0.003274: 170.003274 – 0.003487: 170.003487 – 0.0037: 110.0037 – 0.003913: 70.003913 – 0.004126: 50.004126 – 0.004339: 30.004339 – 0.004552: 50.004552 – 0.004765: 50.004765 – 0.004978: 10.004978 – 0.005191: 30.0000.0020.0040.006
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,053
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.001048 ± 0.000827
Median
?50th percentile: half the non-missing values lie at or below it.
0.0007456
Range
?Smallest and largest recorded non-missing values.
7.847e-05 – 0.005191
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.79
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.9 / 3.9
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

cellulose_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

cellulose_area distribution02505007500.00012 – 0.0004195: 2140.0004195 – 0.000719: 6980.000719 – 0.001019: 3940.001019 – 0.001318: 1550.001318 – 0.001618: 1150.001618 – 0.001917: 1130.001917 – 0.002217: 570.002217 – 0.002516: 310.002516 – 0.002816: 200.002816 – 0.003115: 130.003115 – 0.003415: 180.003415 – 0.003714: 180.003714 – 0.004014: 140.004014 – 0.004313: 90.004313 – 0.004613: 100.004613 – 0.004912: 70.004912 – 0.005212: 40.005212 – 0.005511: 80.005511 – 0.005811: 50.005811 – 0.00611: 40.00611 – 0.00641: 50.00641 – 0.006709: 30.006709 – 0.007009: 20.007009 – 0.007309: 30.0000.0020.0040.0060.008
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,022
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.001102 ± 0.00103
Median
?50th percentile: half the non-missing values lie at or below it.
0.0007478
Range
?Smallest and largest recorded non-missing values.
0.00012 – 0.007309
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.931
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.8 / 9.3
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

lignin_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

lignin_area distribution02004006002.12e-05 – 0.0002101: 4360.0002101 – 0.0003991: 3620.0003991 – 0.000588: 4440.000588 – 0.0007769: 2740.0007769 – 0.0009659: 1060.0009659 – 0.001155: 580.001155 – 0.001344: 250.001344 – 0.001533: 160.001533 – 0.001722: 220.001722 – 0.001911: 310.001911 – 0.002099: 370.002099 – 0.002288: 300.002288 – 0.002477: 150.002477 – 0.002666: 110.002666 – 0.002855: 100.002855 – 0.003044: 70.003044 – 0.003233: 70.003233 – 0.003422: 60.003422 – 0.003611: 40.003611 – 0.0038: 20.0038 – 0.003989: 40.003989 – 0.004178: 30.004178 – 0.004367: 50.004367 – 0.004556: 50.0000.0020.0040.006
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,022
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.0006518 ± 0.000698
Median
?50th percentile: half the non-missing values lie at or below it.
0.0004675
Range
?Smallest and largest recorded non-missing values.
2.12e-05 – 0.004556
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.07
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.6 / 7.8
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

chlA_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

chlA_area distribution02004006008.885e-06 – 2.076e-05: 872.076e-05 – 3.264e-05: 3673.264e-05 – 4.452e-05: 5664.452e-05 – 5.639e-05: 4835.639e-05 – 6.827e-05: 2046.827e-05 – 8.015e-05: 1038.015e-05 – 9.203e-05: 399.203e-05 – 0.0001039: 240.0001039 – 0.0001158: 40.0001158 – 0.0001277: 60.0001277 – 0.0001395: 110.0001395 – 0.0001514: 40.0001514 – 0.0001633: 20.0001633 – 0.0001752: 50.0001752 – 0.000187: 20.000187 – 0.0001989: 00.0001989 – 0.0002108: 40.0002108 – 0.0002227: 20.0002227 – 0.0002346: 10.0002346 – 0.0002464: 00.0002464 – 0.0002583: 00.0002583 – 0.0002702: 00.0002702 – 0.0002821: 00.0002821 – 0.0002939: 10.00000.00010.00020.0003
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,027
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
4.685e-05 ± 2.37e-05
Median
?50th percentile: half the non-missing values lie at or below it.
4.321e-05
Range
?Smallest and largest recorded non-missing values.
8.885e-06 – 0.0002939
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.505
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.2 / 18
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

chlB_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

chlB_area distribution02004006002.971e-06 – 6.79e-06: 706.79e-06 – 1.061e-05: 3461.061e-05 – 1.443e-05: 5371.443e-05 – 1.825e-05: 5061.825e-05 – 2.207e-05: 2272.207e-05 – 2.589e-05: 1022.589e-05 – 2.97e-05: 552.97e-05 – 3.352e-05: 223.352e-05 – 3.734e-05: 123.734e-05 – 4.116e-05: 94.116e-05 – 4.498e-05: 74.498e-05 – 4.88e-05: 54.88e-05 – 5.262e-05: 55.262e-05 – 5.644e-05: 45.644e-05 – 6.026e-05: 16.026e-05 – 6.408e-05: 16.408e-05 – 6.789e-05: 36.789e-05 – 7.171e-05: 17.171e-05 – 7.553e-05: 17.553e-05 – 7.935e-05: 07.935e-05 – 8.317e-05: 08.317e-05 – 8.699e-05: 08.699e-05 – 9.081e-05: 09.081e-05 – 9.463e-05: 10.0000000.0000250.0000500.0000750.000100
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,027
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.562e-05 ± 7.6e-06
Median
?50th percentile: half the non-missing values lie at or below it.
1.446e-05
Range
?Smallest and largest recorded non-missing values.
2.971e-06 – 9.463e-05
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.487
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3 / 17
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

car_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

car_area distribution02505007502.482e-06 – 4.821e-06: 824.821e-06 – 7.159e-06: 3447.159e-06 – 9.497e-06: 6109.497e-06 – 1.184e-05: 4521.184e-05 – 1.417e-05: 2151.417e-05 – 1.651e-05: 1061.651e-05 – 1.885e-05: 381.885e-05 – 2.119e-05: 182.119e-05 – 2.353e-05: 112.353e-05 – 2.586e-05: 82.586e-05 – 2.82e-05: 72.82e-05 – 3.054e-05: 53.054e-05 – 3.288e-05: 53.288e-05 – 3.522e-05: 23.522e-05 – 3.756e-05: 33.756e-05 – 3.989e-05: 43.989e-05 – 4.223e-05: 24.223e-05 – 4.457e-05: 04.457e-05 – 4.691e-05: 14.691e-05 – 4.925e-05: 14.925e-05 – 5.158e-05: 05.158e-05 – 5.392e-05: 05.392e-05 – 5.626e-05: 05.626e-05 – 5.86e-05: 10.000000.000020.000040.00006
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 2,027
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.005e-05 ± 4.7e-06
Median
?50th percentile: half the non-missing values lie at or below it.
9.23e-06
Range
?Smallest and largest recorded non-missing values.
2.482e-06 – 5.86e-05
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.468
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.2 / 18
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Al_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Al_area distribution01002003000 – 1.803e-07: 1551.803e-07 – 3.606e-07: 2343.606e-07 – 5.409e-07: 1235.409e-07 – 7.212e-07: 767.212e-07 – 9.015e-07: 269.015e-07 – 1.082e-06: 211.082e-06 – 1.262e-06: 81.262e-06 – 1.442e-06: 51.442e-06 – 1.623e-06: 71.623e-06 – 1.803e-06: 31.803e-06 – 1.983e-06: 11.983e-06 – 2.164e-06: 12.164e-06 – 2.344e-06: 22.344e-06 – 2.524e-06: 02.524e-06 – 2.705e-06: 02.705e-06 – 2.885e-06: 02.885e-06 – 3.065e-06: 03.065e-06 – 3.246e-06: 03.246e-06 – 3.426e-06: 03.426e-06 – 3.606e-06: 03.606e-06 – 3.786e-06: 03.786e-06 – 3.967e-06: 03.967e-06 – 4.147e-06: 14.147e-06 – 4.327e-06: 10.0000000.0000020.0000040.000006
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,278
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
4.052e-07 ± 3.87e-07
Median
?50th percentile: half the non-missing values lie at or below it.
3.1e-07
Range
?Smallest and largest recorded non-missing values.
0 – 4.327e-06
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.956
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
4 / 29
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Ca_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Ca_area distribution0501001501.26e-05 – 2.782e-05: 502.782e-05 – 4.304e-05: 1134.304e-05 – 5.826e-05: 1175.826e-05 – 7.348e-05: 1267.348e-05 – 8.87e-05: 628.87e-05 – 0.0001039: 420.0001039 – 0.0001191: 420.0001191 – 0.0001344: 300.0001344 – 0.0001496: 190.0001496 – 0.0001648: 150.0001648 – 0.00018: 70.00018 – 0.0001952: 80.0001952 – 0.0002105: 90.0002105 – 0.0002257: 50.0002257 – 0.0002409: 50.0002409 – 0.0002561: 40.0002561 – 0.0002713: 50.0002713 – 0.0002866: 40.0002866 – 0.0003018: 10.0003018 – 0.000317: 00.000317 – 0.0003322: 00.0003322 – 0.0003474: 00.0003474 – 0.0003627: 00.0003627 – 0.0003779: 10.00000.00010.00020.00030.0004
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,277
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
7.941e-05 ± 5.33e-05
Median
?50th percentile: half the non-missing values lie at or below it.
6.45e-05
Range
?Smallest and largest recorded non-missing values.
1.26e-05 – 0.0003779
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.671
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.8 / 3.8
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Cu_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Cu_area distribution0501001500 – 1.088e-08: 291.088e-08 – 2.176e-08: 492.176e-08 – 3.263e-08: 1153.263e-08 – 4.351e-08: 904.351e-08 – 5.439e-08: 1125.439e-08 – 6.527e-08: 1066.527e-08 – 7.615e-08: 907.615e-08 – 8.703e-08: 348.703e-08 – 9.79e-08: 229.79e-08 – 1.088e-07: 51.088e-07 – 1.197e-07: 21.197e-07 – 1.305e-07: 11.305e-07 – 1.414e-07: 11.414e-07 – 1.523e-07: 11.523e-07 – 1.632e-07: 21.632e-07 – 1.741e-07: 01.741e-07 – 1.849e-07: 11.849e-07 – 1.958e-07: 01.958e-07 – 2.067e-07: 02.067e-07 – 2.176e-07: 02.176e-07 – 2.284e-07: 12.284e-07 – 2.393e-07: 02.393e-07 – 2.502e-07: 02.502e-07 – 2.611e-07: 10.00000000.00000010.00000020.0000003
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,280
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
4.908e-08 ± 2.67e-08
Median
?50th percentile: half the non-missing values lie at or below it.
4.741e-08
Range
?Smallest and largest recorded non-missing values.
0 – 2.611e-07
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.544
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.6 / 9.4
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Fe_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Fe_area distribution01002001.799e-07 – 2.885e-07: 702.885e-07 – 3.972e-07: 1833.972e-07 – 5.058e-07: 1675.058e-07 – 6.145e-07: 996.145e-07 – 7.231e-07: 547.231e-07 – 8.318e-07: 358.318e-07 – 9.404e-07: 209.404e-07 – 1.049e-06: 151.049e-06 – 1.158e-06: 81.158e-06 – 1.266e-06: 31.266e-06 – 1.375e-06: 41.375e-06 – 1.484e-06: 01.484e-06 – 1.592e-06: 11.592e-06 – 1.701e-06: 21.701e-06 – 1.81e-06: 11.81e-06 – 1.918e-06: 01.918e-06 – 2.027e-06: 02.027e-06 – 2.135e-06: 02.135e-06 – 2.244e-06: 02.244e-06 – 2.353e-06: 02.353e-06 – 2.461e-06: 02.461e-06 – 2.57e-06: 02.57e-06 – 2.679e-06: 02.679e-06 – 2.787e-06: 20.0000000.0000010.0000020.000003
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,278
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
5.063e-07 ± 2.55e-07
Median
?50th percentile: half the non-missing values lie at or below it.
4.329e-07
Range
?Smallest and largest recorded non-missing values.
1.799e-07 – 2.787e-06
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.504
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.2 / 20
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

K_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

K_area distribution01002001.482e-05 – 2.349e-05: 242.349e-05 – 3.215e-05: 1283.215e-05 – 4.082e-05: 1814.082e-05 – 4.948e-05: 1194.948e-05 – 5.814e-05: 815.814e-05 – 6.681e-05: 496.681e-05 – 7.547e-05: 197.547e-05 – 8.414e-05: 158.414e-05 – 9.28e-05: 159.28e-05 – 0.0001015: 50.0001015 – 0.0001101: 40.0001101 – 0.0001188: 60.0001188 – 0.0001275: 40.0001275 – 0.0001361: 70.0001361 – 0.0001448: 20.0001448 – 0.0001535: 30.0001535 – 0.0001621: 20.0001621 – 0.0001708: 00.0001708 – 0.0001794: 00.0001794 – 0.0001881: 00.0001881 – 0.0001968: 00.0001968 – 0.0002054: 00.0002054 – 0.0002141: 00.0002141 – 0.0002228: 10.00000.00010.00020.0003
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,277
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
4.735e-05 ± 2.39e-05
Median
?50th percentile: half the non-missing values lie at or below it.
4.074e-05
Range
?Smallest and largest recorded non-missing values.
1.482e-05 – 0.0002228
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.505
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.4 / 8.5
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Mg_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Mg_area distribution0501001503.179e-06 – 6.455e-06: 106.455e-06 – 9.73e-06: 939.73e-06 – 1.301e-05: 1491.301e-05 – 1.628e-05: 1321.628e-05 – 1.956e-05: 821.956e-05 – 2.283e-05: 712.283e-05 – 2.611e-05: 462.611e-05 – 2.938e-05: 162.938e-05 – 3.266e-05: 193.266e-05 – 3.593e-05: 83.593e-05 – 3.921e-05: 73.921e-05 – 4.248e-05: 94.248e-05 – 4.576e-05: 54.576e-05 – 4.903e-05: 44.903e-05 – 5.231e-05: 25.231e-05 – 5.559e-05: 55.559e-05 – 5.886e-05: 35.886e-05 – 6.214e-05: 26.214e-05 – 6.541e-05: 06.541e-05 – 6.869e-05: 16.869e-05 – 7.196e-05: 07.196e-05 – 7.524e-05: 07.524e-05 – 7.851e-05: 07.851e-05 – 8.179e-05: 10.000000.000020.000040.000060.000080.00010
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,277
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.761e-05 ± 9.91e-06
Median
?50th percentile: half the non-missing values lie at or below it.
1.509e-05
Range
?Smallest and largest recorded non-missing values.
3.179e-06 – 8.179e-05
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.563
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.2 / 6.5
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Mn_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Mn_area distribution01002003000 – 6.749e-07: 2956.749e-07 – 1.35e-06: 1301.35e-06 – 2.025e-06: 622.025e-06 – 2.7e-06: 522.7e-06 – 3.375e-06: 303.375e-06 – 4.049e-06: 274.049e-06 – 4.724e-06: 124.724e-06 – 5.399e-06: 65.399e-06 – 6.074e-06: 96.074e-06 – 6.749e-06: 66.749e-06 – 7.424e-06: 77.424e-06 – 8.099e-06: 28.099e-06 – 8.774e-06: 48.774e-06 – 9.449e-06: 39.449e-06 – 1.012e-05: 51.012e-05 – 1.08e-05: 41.08e-05 – 1.147e-05: 11.147e-05 – 1.215e-05: 11.215e-05 – 1.282e-05: 11.282e-05 – 1.35e-05: 11.35e-05 – 1.417e-05: 31.417e-05 – 1.485e-05: 01.485e-05 – 1.552e-05: 11.552e-05 – 1.62e-05: 30.0000000.0000050.0000100.0000150.000020
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,277
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.783e-06 ± 2.5e-06
Median
?50th percentile: half the non-missing values lie at or below it.
7.996e-07
Range
?Smallest and largest recorded non-missing values.
0 – 1.62e-05
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.4
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.9 / 10
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Na_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Na_area distribution01002003000 – 2.899e-06: 1662.899e-06 – 5.799e-06: 2045.799e-06 – 8.698e-06: 1358.698e-06 – 1.16e-05: 671.16e-05 – 1.45e-05: 251.45e-05 – 1.74e-05: 51.74e-05 – 2.029e-05: 72.029e-05 – 2.319e-05: 42.319e-05 – 2.609e-05: 42.609e-05 – 2.899e-05: 42.899e-05 – 3.189e-05: 53.189e-05 – 3.479e-05: 63.479e-05 – 3.769e-05: 93.769e-05 – 4.059e-05: 44.059e-05 – 4.349e-05: 74.349e-05 – 4.639e-05: 24.639e-05 – 4.929e-05: 24.929e-05 – 5.219e-05: 25.219e-05 – 5.509e-05: 45.509e-05 – 5.799e-05: 15.799e-05 – 6.088e-05: 06.088e-05 – 6.378e-05: 06.378e-05 – 6.668e-05: 06.668e-05 – 6.958e-05: 20.000000.000020.000040.000060.00008
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,277
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
8.037e-06 ± 1.02e-05
Median
?50th percentile: half the non-missing values lie at or below it.
5.235e-06
Range
?Smallest and largest recorded non-missing values.
0 – 6.958e-05
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.27
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.9 / 9.3
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

P_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

P_area distribution01002003003.089e-06 – 5.992e-06: 415.992e-06 – 8.896e-06: 2208.896e-06 – 1.18e-05: 1881.18e-05 – 1.47e-05: 841.47e-05 – 1.761e-05: 291.761e-05 – 2.051e-05: 272.051e-05 – 2.341e-05: 262.341e-05 – 2.632e-05: 122.632e-05 – 2.922e-05: 102.922e-05 – 3.212e-05: 63.212e-05 – 3.503e-05: 63.503e-05 – 3.793e-05: 43.793e-05 – 4.083e-05: 54.083e-05 – 4.374e-05: 44.374e-05 – 4.664e-05: 04.664e-05 – 4.954e-05: 04.954e-05 – 5.245e-05: 05.245e-05 – 5.535e-05: 05.535e-05 – 5.825e-05: 05.825e-05 – 6.116e-05: 16.116e-05 – 6.406e-05: 16.406e-05 – 6.696e-05: 06.696e-05 – 6.987e-05: 06.987e-05 – 7.277e-05: 10.000000.000020.000040.000060.00008
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,277
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.217e-05 ± 7.68e-06
Median
?50th percentile: half the non-missing values lie at or below it.
9.853e-06
Range
?Smallest and largest recorded non-missing values.
3.089e-06 – 7.277e-05
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.631
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.9 / 13
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Zn_area

target · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

Zn_area distribution01002003002.297e-08 – 1.424e-07: 2421.424e-07 – 2.619e-07: 1272.619e-07 – 3.813e-07: 343.813e-07 – 5.007e-07: 295.007e-07 – 6.202e-07: 346.202e-07 – 7.396e-07: 227.396e-07 – 8.591e-07: 368.591e-07 – 9.785e-07: 229.785e-07 – 1.098e-06: 221.098e-06 – 1.217e-06: 91.217e-06 – 1.337e-06: 141.337e-06 – 1.456e-06: 121.456e-06 – 1.576e-06: 161.576e-06 – 1.695e-06: 71.695e-06 – 1.815e-06: 131.815e-06 – 1.934e-06: 41.934e-06 – 2.053e-06: 52.053e-06 – 2.173e-06: 32.173e-06 – 2.292e-06: 32.292e-06 – 2.412e-06: 32.412e-06 – 2.531e-06: 12.531e-06 – 2.651e-06: 32.651e-06 – 2.77e-06: 12.77e-06 – 2.89e-06: 20.0000000.0000010.0000020.000003
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 3,278
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
4.988e-07 ± 5.73e-07
Median
?50th percentile: half the non-missing values lie at or below it.
2.057e-07
Range
?Smallest and largest recorded non-missing values.
2.297e-08 – 2.89e-06
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.15
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.6 / 2.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Metadata 14

ecosis_resource_id

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

ecosis_resource_id classesa8f5093c-4383-40ad-85ae-4ad0d…a8f5093c-4383-40ad-85ae-4ad0d7a22eff: 1,9711,9716e1dc4ab-be82-4ab4-8824-10468…6e1dc4ab-be82-4ab4-8824-10468ce6bd04: 1,9711,971
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
2
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
1
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
1
Top class
?Most frequent recorded category and its observation count.
a8f5093c-4383-40ad-85ae-4ad0d7a22eff (1,971)

site

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

site classesIdB_ile_ste_margIdB_ile_ste_marg: 520520GroboisFieldELGroboisFieldEL: 490490MtMeg-1MtMeg-1: 408408CGOP_1CGOP_1: 402402MSB_CheminMSB_Chemin: 220220Frayere_maraisFrayere_marais: 126126Oka_PlageOka_Plage: 122122SBLUdeMSBLUdeM: 120120SWA-WarrenSWA-Warren: 116116SBLUdeM-fSBLUdeM-f: 108108+10 more+10 more: 632632
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
47
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.83
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
260
Top class
?Most frequent recorded category and its observation count.
IdB_ile_ste_marg (520)

latitude

metadata · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

latitude distribution02,0004,000-34.81 – -31.32: 136-31.32 – -27.84: 0-27.84 – -24.36: 0-24.36 – -20.87: 0-20.87 – -17.39: 0-17.39 – -13.9: 0-13.9 – -10.42: 0-10.42 – -6.936: 0-6.936 – -3.452: 0-3.452 – 0.03253: 00.03253 – 3.517: 03.517 – 7.001: 07.001 – 10.48: 010.48 – 13.97: 013.97 – 17.45: 017.45 – 20.94: 020.94 – 24.42: 024.42 – 27.91: 027.91 – 31.39: 031.39 – 34.87: 034.87 – 38.36: 038.36 – 41.84: 041.84 – 45.33: 4045.33 – 48.81: 3766-50-2502550
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
43.16 ± 14.7
Median
?50th percentile: half the non-missing values lie at or below it.
45.59
Range
?Smallest and largest recorded non-missing values.
-34.81 – 48.81
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.342
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-5.1 / 24
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

longitude

metadata · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

longitude distribution01,0002,0003,000-123.7 – -113.7: 402-113.7 – -103.7: 0-103.7 – -93.69: 0-93.69 – -83.7: 0-83.7 – -73.71: 824-73.71 – -63.73: 2580-63.73 – -53.74: 0-53.74 – -43.75: 0-43.75 – -33.76: 0-33.76 – -23.77: 0-23.77 – -13.78: 0-13.78 – -3.794: 0-3.794 – 6.195: 06.195 – 16.18: 016.18 – 26.17: 026.17 – 36.16: 036.16 – 46.15: 046.15 – 56.14: 056.14 – 66.13: 066.13 – 76.12: 076.12 – 86.1: 086.1 – 96.09: 096.09 – 106.1: 0106.1 – 116.1: 136-200-1000100200
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
-71.93 ± 38.6
Median
?50th percentile: half the non-missing values lie at or below it.
-73.47
Range
?Smallest and largest recorded non-missing values.
-123.7 – 116.1
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.537
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.7 / 17
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

date

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

date classes2019-07-252019-07-25: 74742018-07-242018-07-24: 62622019-07-242019-07-24: 62622019-07-092019-07-09: 60602019-07-102019-07-10: 60602019-05-122019-05-12: 60602019-07-182019-07-18: 58582019-05-112019-05-11: 58582018-07-252018-07-25: 56562019-08-132019-08-13: 5656+10 more+10 more: 510510
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
130
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.97
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
37
Top class
?Most frequent recorded category and its observation count.
2019-07-25 (74)

signal_type

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

signal_type classesabsorbanceabsorbance: 1,9711,971transmittancetransmittance: 1,9711,971
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
2
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
1
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
1
Top class
?Most frequent recorded category and its observation count.
absorbance (1,971)

source_sample_id

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

source_sample_id classes81333118133311: 2285593558559355: 2285608808560880: 2285623628562362: 2285634668563466: 2285646358564635: 2291538999153899: 2291551139155113: 2291562399156239: 2291572969157296: 22+10 more+10 more: 2020
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
1,971
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
1
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
1
Top class
?Most frequent recorded category and its observation count.
8133311 (2)

source_measurement.date

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

source_measurement.date classes2019-07-252019-07-25: 74742018-07-242018-07-24: 62622019-07-242019-07-24: 62622019-07-092019-07-09: 60602019-07-102019-07-10: 60602019-05-122019-05-12: 60602019-07-182019-07-18: 58582019-05-112019-05-11: 58582018-07-252018-07-25: 56562019-08-132019-08-13: 5656+10 more+10 more: 510510
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
130
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.97
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
37
Top class
?Most frequent recorded category and its observation count.
2019-07-25 (74)

source_project

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

source_project classes2018-BeauchampRioux-MSc-UdeM2018-BeauchampRioux-MSc-UdeM: 8728722019-Blanchard-MSc-UdeM2019-Blanchard-MSc-UdeM: 6826822019-Phragmites-temporal2019-Phragmites-temporal: 6006002019-Crofts-PhD-UdeS2019-Crofts-PhD-UdeS: 4084082018-Hacker-PhD-UBC2018-Hacker-PhD-UBC: 4024022019-Boucherville2019-Boucherville: 3463462018-Girard-MSc-UdeM2018-Girard-MSc-UdeM: 1901902018-Boucherville2018-Boucherville: 1441442019-CABO-General2019-CABO-General: 142142SWA-WarrenSWA-Warren: 136136+1 more+1 more: 2020
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
11
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.89
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
4e+01
Top class
?Most frequent recorded category and its observation count.
2018-BeauchampRioux-MSc-UdeM (872)

source_site

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

source_site classesIdB_ile_ste_margIdB_ile_ste_marg: 520520GroboisFieldELGroboisFieldEL: 490490MtMeg-1MtMeg-1: 408408CGOP_1CGOP_1: 402402MSB_CheminMSB_Chemin: 220220Frayere_maraisFrayere_marais: 126126Oka_PlageOka_Plage: 122122SBLUdeMSBLUdeM: 120120SWA-WarrenSWA-Warren: 116116SBLUdeM-fSBLUdeM-f: 108108+10 more+10 more: 632632
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
47
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.83
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
260
Top class
?Most frequent recorded category and its observation count.
IdB_ile_ste_marg (520)

source_stage

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

source_stage classesNANA: 3,8063,806Stage 5 UnburntStage 5 Unburnt: 2020Stage 2Stage 2: 2020Stage 3Stage 3: 2020Stage 4Stage 4: 2020Stage 1Stage 1: 2020Stage 6Stage 6: 2020Stage 5 BurntStage 5 Burnt: 1616
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Classes
?Number of distinct recorded category values.
8
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.1
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
2e+02
Top class
?Most frequent recorded category and its observation count.
NA (3,806)

source_latitude

metadata · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

source_latitude distribution02,0004,000-34.81 – -31.32: 136-31.32 – -27.84: 0-27.84 – -24.36: 0-24.36 – -20.87: 0-20.87 – -17.39: 0-17.39 – -13.9: 0-13.9 – -10.42: 0-10.42 – -6.936: 0-6.936 – -3.452: 0-3.452 – 0.03253: 00.03253 – 3.517: 03.517 – 7.001: 07.001 – 10.48: 010.48 – 13.97: 013.97 – 17.45: 017.45 – 20.94: 020.94 – 24.42: 024.42 – 27.91: 027.91 – 31.39: 031.39 – 34.87: 034.87 – 38.36: 038.36 – 41.84: 041.84 – 45.33: 4045.33 – 48.81: 3766-50-2502550
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
43.16 ± 14.7
Median
?50th percentile: half the non-missing values lie at or below it.
45.59
Range
?Smallest and largest recorded non-missing values.
-34.81 – 48.81
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.342
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-5.1 / 24
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

source_longitude

metadata · numeric

Read the recorded value distribution and summary statistics; no measurement unit is recorded.

source_longitude distribution01,0002,0003,000-123.7 – -113.7: 402-113.7 – -103.7: 0-103.7 – -93.69: 0-93.69 – -83.7: 0-83.7 – -73.71: 824-73.71 – -63.73: 2580-63.73 – -53.74: 0-53.74 – -43.75: 0-43.75 – -33.76: 0-33.76 – -23.77: 0-23.77 – -13.78: 0-13.78 – -3.794: 0-3.794 – 6.195: 06.195 – 16.18: 016.18 – 26.17: 026.17 – 36.16: 036.16 – 46.15: 046.15 – 56.14: 056.14 – 66.13: 066.13 – 76.12: 076.12 – 86.1: 086.1 – 96.09: 096.09 – 106.1: 0106.1 – 116.1: 136-200-1000100200
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
-71.93 ± 38.6
Median
?50th percentile: half the non-missing values lie at or below it.
-73.47
Range
?Smallest and largest recorded non-missing values.
-123.7 – 116.1
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.537
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.7 / 17
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

source_order

metadata · categorical

Compare recorded category counts and class balance. Bar lengths show observations in each displayed category.

source_order classesPoalesPoales: 359359FagalesFagales: 355355SapindalesSapindales: 271271MalpighialesMalpighiales: 198198RosalesRosales: 149149PinalesPinales: 114114AsteralesAsterales: 111111MyrtalesMyrtales: 7474EricalesEricales: 7272LamialesLamiales: 5555+10 more+10 more: 196196
n / missing
?Recorded observation count and number of missing values for this variable.
3,942 / 1,971
Classes
?Number of distinct recorded category values.
22
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.8
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
5e+01
Top class
?Most frequent recorded category and its observation count.
Poales (359)
Constant metadata 16

Fields with one recorded value provide context for every observation; they have no distribution to compare.

  • coordinate_precision_notessource-provided coordinates when available
  • year2,022
  • plant_partLeaf
  • canopy_or_leafleaf
  • instrumentSpectra Vista Corporation HR-1024i
  • acquisition_modeContact
  • axis_unitnm
  • axis_min400
  • axis_max2,400
  • n_points_original2,001
  • publication_doi10.1016/j.rse.2023.113926 | 10.1080/00103624.2016.1228952 | 10.1111/1365-2745.13972 | 10.1111/nph.18713 | 10.1186/s13007-021-00816-4 | 10.17504/protocols.io.q26g7rn23vwz/v2 | 10.21232/44vxHorW | 10.21232/44vxhorw | 10.21232/58kApoRy | 10.21232/deP7jVyq | 10.21232/dep7jvyq | 10.5281/zenodo.10735410 | 10.5683/SP3/NYABAG
  • citationShan Kothari, Rosalie Beauchamp-Rioux, Florence Blanchard, Anna L. Crofts, Alize Girard, Xavier Guilbeault-Mayers, Paul W. Hacker, Juliana Pardo, Anna K. Schweiger, Sabrina Demers-Thibeault, Anne Bruneau, Nicholas C. Coops, Margaret Kalacska, Mark Vellend and Etienne Lalibert. 2022. CABO 2018-2019 Leaf-Level Spectra v2. Data set. Available on-line [http://ecosis.org] from the Ecological Spectral Information System (EcoSIS). 10.21232/58kApoRy
  • licenseCreative Commons Attribution
  • rights_statusexplicit_open
  • usage_scopepublic_reuse_possible
  • notesEcoSIS package cabo-2018-2019-leaf-level-spectra-v2, no interpolation applied by project.

Alignment

How observations join to physical sample IDs. Multiple exported rows are not necessarily independent samples or technical repetitions. Reading guide

Alignment levelsample
Sample id availableyes
Samples1,971
Observations (total)3,942
Exported observations per unitmin 1 · mean 1 · max 1
Identity statusavailable
Documented technical repetitionsND
Source unitMultiplicity of the declared identifier; protocol not established

Splits

Partitions supplied by the original dataset. They are documented here and are not applied automatically when loading. Reading guide

No original partition summaries are recorded. Loading does not create a train/test split.

Load this dataset

Use the appropriate route below: an assembled dataset, original raw resources, or the documented access procedure. Reading guide

# pip install nirs4all-datasets
from nirs4all_datasets import get

ds = get("ecosis_cabo_2018_2019_leaf_level_spectra_v2_nirs")            # DOI-pinned, checksum-verified, cached
X, y = ds.x(), ds.y()
print(X.shape, y.shape)
card.jsoncroissant.jsonIdentity metadata only — the dataset bytes live at the origin / DOI.

Read the documentation

Access and rights are separate

Start with provenance and governance at the top of a card. Provenance links to the original resources and publications. Governance records the license, redistribution conditions and content identity.

Open source access means an open original-source route is recorded. Restricted redistribution is the display label for the catalog's private tier: rights are restricted or not cleared for redistribution. It does not mean that the original source is necessarily private.

Raw reproducible identifies a retrieval route. Assembly incomplete means raw resources can be available while dataset-specific conversion is missing. The loading example uses retrieve(id, prepare=False) for these raw downloads; it returns resource metadata rather than X/Y arrays. A complete original-source recipe uses get(id). Two Harvard datasets require explicit guestbook answers.

Token required means no open automatic route is recorded. A Dataverse token works only once the canonical data have a configured hosted DOI. Manual access requires the original provider's documented steps. Availability labels describe the catalog routes, not a fresh live check of every URL.

Why is PCA on a dataset card?

Spectra have many correlated wavelengths. Principal component analysis (PCA) compresses their variation into a few orthogonal directions, called principal components (PCs). It is an exploratory summary of X, calculated without using the target Y.

The score plot places each plotted observation on PC1 and PC2. Nearby dots have similar projections; groups can reveal batches, instruments or natural subpopulations. Axis percentages show explained spectral variance. Large sources are sampled to at most 800 observations. Similar positions in two dimensions do not guarantee similar full spectra; an isolated dot does not prove an acquisition fault.

The scree plot reports spectral variance per component, helping you see whether variation is concentrated in a few dimensions. It is not explained target variance or predictive accuracy. The scree projection and score-plot projection may use different row samples; their percentages need not match.

Q / SPE measures residual variation outside the retained PCA subspace. Hotelling T² measures an observation's scaled distance within that subspace; Mahalanobis H summarizes PCA-space distance. The displayed p95/median ratios compare the distribution's upper tail with its center, without an absolute rejection threshold.

Historical profiles replace missing cells with column medians before PCA, center channels, and use bounded row/component counts. Loadings and distances depend on signal units and preprocessing. Compare compatible sources and inspect the original spectra before acting.

Scores, evidence and missing values

Read measured values first. An alert score maps selected metrics to a heuristic 0–1 scale. The display bands are weak below 0.42, medium from 0.42 to below 0.72, and strong from 0.72. They are not universally validated pass/fail thresholds.

The radar's center is 0 and its outer ring is 1: outward means a stronger anomaly or heterogeneity signal for that axis. Its table gives values rounded to two decimals and explains each axis. Missing axes are left blank; partial profiles have no filled polygon. The mean profile score averages only available axes and is not an overall quality grade.

Diagnostic bars rank possible explanations from heuristic signatures. A score of 0.78 does not mean a 78% causal probability. Evidence coverage is the proportion of required signals available, not confidence in the cause. A dash or “unavailable” means the quantity could not be computed; zero is an actual recorded value.

RMS (root mean square distance) and SAM (Spectral Angle Mapper, in radians) use this dataset's mean spectrum as their reference. They do not compare with an independently acquired white or dark reference. Repeated IDs require a documented protocol before within-ID spread can be called technical repeatability.

X–Y plots show Pearson correlation within this dataset. They identify linear associations; they are not cross-validated predictions and do not establish causal relationships. Targets, metadata, observation counts and physical sample counts have different meanings.

Open the full reading guide