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Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR

zenodo · NIR

Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR. Origin database composed from 2 standardized v2.0 leaves: 2 spectral source(s), 1 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2zenodo
768
samples
2,276
wavelengths
2
sources
1
targets
19
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

ContributorTwinSpectra Dataset
Conversion statuspartial
Origin · zenodo [open]https://zenodo.org/records/18471662 — Zenodo
Origin · zenodo [open]https://zenodo.org/api/records/18471662/files/measurements_2151.csv/content — Zenodo
Origin · zenodo [open]https://zenodo.org/api/records/18471662/files/measurements_125.csv/content — Zenodo

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.
RedistributionZenodo record license is CC-BY-4.0; redistribution/publication reuse allowed with attribution.
Content version1.1.0
Schema / protocol2.0
Content hash6a3812c17d553345…
Processing hash66d2540a3fe0a6fa…
Metadata hasheadd30287fc0055f…

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 score0.61
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.

Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureZenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR — integrity: 0.00Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR — noise: 0.00Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR — artefacts: 1.00Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR — baseline: 0.27Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR — PCA outliers: 1.00Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR — reference: 1.00Zenodo TwinSpectra soil NIR, ASD FieldSpec and MicroNIR — structure: 1.00Zenodo TwinSpec…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.
0.27
PCA outliers
?Combines relative PCA residual and score-distance tails. Valid rare spectra can produce a high value.
1.00
Distance to average spectrum
?Dispersion around this dataset's mean spectrum, using distance, shape and shift summaries.
1.00
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.
1.00

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: 0.940.94Signature compatible with a population shiftSignature compatible with a population shift: 0.660.66Offset compatible with a different white referenceOffset compatible with a different white reference: 0.620.62Signature compatible with a different backgroundSignature compatible with a different background: 0.560.56High spectral roughness signatureHigh spectral roughness signature: 0.440.44Signature compatible with clippingSignature compatible with clipping: 0.380.38Flat spectrum/weak signalFlat spectrum/weak signal: 0.200.20

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_fieldspec0.94strong100 %PCA Q 1.00, Spike rate 1.00, Jump rate 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_fieldspec0.66medium100 %RMS/SAM to mean spectrum 1.00, PCA structure 1.00, Mahalanobis / T2 0.81Different 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_micronir0.62medium100 %PCA Q 1.00, RMS/SAM to mean spectrum 1.00, local artifacts 1.00Systematic 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_micronir0.56medium100 %PCA Q 1.00, RMS/SAM to mean spectrum 1.00, Mahalanobis / T2 0.78Systematic 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_micronir0.44medium100 %PCA Q 1.00, Spike rate 1.00, RMS/SAM to mean spectrum 1.00Weak 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_micronir0.38weak100 %PCA Q 1.00, Jump rate 1.00, Baseline/mean/area 0.30Detector 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_fieldspec0.20weak100 %PCA Q 1.00Bad 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_fieldspec—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
ASD FieldSpec 4 Hi-Res718718
Viavi microNIR720720

670 sample units are measured by every source; 98 by a single source. Sources are joined by declared sample identity, never by row position.

ASD FieldSpec 4 Hi-Res

X_fieldspec · NIR · ASD FieldSpec 4 Hi-Res

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.

ASD FieldSpec 4 Hi-Res spectra0.00.20.40.60.801,0002,0003,000q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm350nm — median 0.1261 (q25–q75 0.06688–0.2152)365nm — median 0.09917 (q25–q75 0.05829–0.1549)381nm — median 0.08907 (q25–q75 0.05353–0.134)396nm — median 0.1004 (q25–q75 0.05723–0.1569)412nm — median 0.1101 (q25–q75 0.06107–0.1884)427nm — median 0.1154 (q25–q75 0.06443–0.2049)443nm — median 0.1209 (q25–q75 0.06822–0.218)458nm — median 0.1282 (q25–q75 0.07148–0.2284)474nm — median 0.1376 (q25–q75 0.07359–0.241)489nm — median 0.1472 (q25–q75 0.0752–0.2506)505nm — median 0.1556 (q25–q75 0.07665–0.2612)520nm — median 0.1595 (q25–q75 0.07775–0.2664)536nm — median 0.1628 (q25–q75 0.07975–0.2703)551nm — median 0.1633 (q25–q75 0.08115–0.2721)567nm — median 0.1621 (q25–q75 0.08095–0.2753)582nm — median 0.1654 (q25–q75 0.08382–0.2836)597nm — median 0.1676 (q25–q75 0.0882–0.2942)613nm — median 0.1715 (q25–q75 0.08877–0.3004)628nm — median 0.1738 (q25–q75 0.08993–0.3077)644nm — median 0.1789 (q25–q75 0.09272–0.3119)659nm — median 0.186 (q25–q75 0.09494–0.32)675nm — median 0.1871 (q25–q75 0.09628–0.3234)690nm — median 0.1924 (q25–q75 0.09846–0.3284)706nm — median 0.1954 (q25–q75 0.1043–0.3324)721nm — median 0.1996 (q25–q75 0.1086–0.3378)737nm — median 0.2093 (q25–q75 0.1142–0.3469)752nm — median 0.2205 (q25–q75 0.1212–0.3587)768nm — median 0.2303 (q25–q75 0.1243–0.373)783nm — median 0.2427 (q25–q75 0.1253–0.3757)799nm — median 0.2439 (q25–q75 0.1288–0.3828)814nm — median 0.2498 (q25–q75 0.1335–0.3908)829nm — median 0.2542 (q25–q75 0.1376–0.3983)845nm — median 0.2576 (q25–q75 0.1389–0.4001)860nm — median 0.2619 (q25–q75 0.1388–0.4012)876nm — median 0.2629 (q25–q75 0.1418–0.406)891nm — median 0.2643 (q25–q75 0.1456–0.4093)907nm — median 0.2653 (q25–q75 0.1462–0.4098)922nm — median 0.2674 (q25–q75 0.1485–0.4106)938nm — median 0.2691 (q25–q75 0.1496–0.415)953nm — median 0.2695 (q25–q75 0.1508–0.4188)969nm — median 0.2709 (q25–q75 0.1518–0.4211)984nm — median 0.2728 (q25–q75 0.1525–0.4247)1,000nm — median 0.2744 (q25–q75 0.1532–0.4272)1,015nm — median 0.2629 (q25–q75 0.1493–0.4073)1,031nm — median 0.2638 (q25–q75 0.1496–0.4086)1,046nm — median 0.2672 (q25–q75 0.1518–0.4149)1,062nm — median 0.2688 (q25–q75 0.1508–0.4149)1,077nm — median 0.2673 (q25–q75 0.1502–0.4111)1,092nm — median 0.2657 (q25–q75 0.1493–0.4096)1,108nm — median 0.2646 (q25–q75 0.1484–0.407)1,123nm — median 0.2654 (q25–q75 0.1472–0.4069)1,139nm — median 0.2651 (q25–q75 0.1458–0.4063)1,154nm — median 0.2637 (q25–q75 0.1462–0.4059)1,170nm — median 0.2619 (q25–q75 0.1447–0.4018)1,185nm — median 0.2611 (q25–q75 0.141–0.3938)1,201nm — median 0.2589 (q25–q75 0.1392–0.3882)1,216nm — median 0.2578 (q25–q75 0.1386–0.3892)1,232nm — median 0.262 (q25–q75 0.1445–0.3976)1,247nm — median 0.2663 (q25–q75 0.1448–0.4088)1,263nm — median 0.2669 (q25–q75 0.1451–0.4138)1,278nm — median 0.2693 (q25–q75 0.1466–0.4166)1,294nm — median 0.2693 (q25–q75 0.146–0.4146)1,309nm — median 0.2653 (q25–q75 0.1444–0.4127)1,324nm — median 0.2618 (q25–q75 0.1444–0.4113)1,340nm — median 0.2603 (q25–q75 0.144–0.4101)1,355nm — median 0.2581 (q25–q75 0.1431–0.4048)1,371nm — median 0.2561 (q25–q75 0.1417–0.3946)1,386nm — median 0.2544 (q25–q75 0.138–0.3889)1,402nm — median 0.254 (q25–q75 0.1359–0.3844)1,417nm — median 0.2503 (q25–q75 0.1349–0.3779)1,433nm — median 0.2478 (q25–q75 0.1342–0.3771)1,448nm — median 0.2481 (q25–q75 0.1355–0.3775)1,464nm — median 0.2494 (q25–q75 0.1365–0.3802)1,479nm — median 0.247 (q25–q75 0.1371–0.3798)1,495nm — median 0.2477 (q25–q75 0.1377–0.3809)1,510nm — median 0.2497 (q25–q75 0.1385–0.3805)1,526nm — median 0.252 (q25–q75 0.1392–0.3817)1,541nm — median 0.253 (q25–q75 0.1396–0.3826)1,556nm — median 0.2545 (q25–q75 0.1401–0.3866)1,572nm — median 0.2551 (q25–q75 0.1405–0.3878)1,587nm — median 0.2565 (q25–q75 0.1408–0.3881)1,603nm — median 0.2578 (q25–q75 0.1404–0.3914)1,618nm — median 0.2573 (q25–q75 0.1402–0.3924)1,634nm — median 0.2534 (q25–q75 0.1382–0.3921)1,649nm — median 0.2517 (q25–q75 0.1367–0.3854)1,665nm — median 0.2466 (q25–q75 0.1337–0.3726)1,680nm — median 0.24 (q25–q75 0.1304–0.3673)1,696nm — median 0.2238 (q25–q75 0.1218–0.3488)1,711nm — median 0.2135 (q25–q75 0.111–0.3447)1,727nm — median 0.1992 (q25–q75 0.1076–0.3349)1,742nm — median 0.2159 (q25–q75 0.1163–0.3488)1,758nm — median 0.2172 (q25–q75 0.1175–0.354)1,773nm — median 0.2236 (q25–q75 0.1201–0.3587)1,788nm — median 0.2343 (q25–q75 0.1236–0.3635)1,804nm — median 0.2226 (q25–q75 0.1195–0.3508)1,819nm — median 0.2234 (q25–q75 0.1194–0.3528)1,835nm — median 0.2245 (q25–q75 0.1202–0.3563)1,850nm — median 0.2315 (q25–q75 0.1222–0.3604)1,866nm — median 0.2323 (q25–q75 0.1232–0.3615)1,881nm — median 0.2302 (q25–q75 0.124–0.3584)1,897nm — median 0.2187 (q25–q75 0.1217–0.3446)1,912nm — median 0.2095 (q25–q75 0.1211–0.3304)1,928nm — median 0.2066 (q25–q75 0.1199–0.3231)1,943nm — median 0.2063 (q25–q75 0.1204–0.3233)1,959nm — median 0.2122 (q25–q75 0.1219–0.329)1,974nm — median 0.2142 (q25–q75 0.1229–0.3356)1,990nm — median 0.2163 (q25–q75 0.1224–0.3421)2,005nm — median 0.2193 (q25–q75 0.1228–0.3438)2,021nm — median 0.2192 (q25–q75 0.1244–0.3425)2,036nm — median 0.2166 (q25–q75 0.1254–0.338)2,051nm — median 0.2142 (q25–q75 0.1251–0.3303)2,067nm — median 0.2114 (q25–q75 0.1242–0.3301)2,082nm — median 0.2094 (q25–q75 0.1227–0.3301)2,098nm — median 0.2096 (q25–q75 0.1228–0.3298)2,113nm — median 0.2086 (q25–q75 0.1226–0.3259)2,129nm — median 0.2091 (q25–q75 0.122–0.3222)2,144nm — median 0.2098 (q25–q75 0.1204–0.3199)2,160nm — median 0.2076 (q25–q75 0.1184–0.3178)2,175nm — median 0.207 (q25–q75 0.1181–0.32)2,191nm — median 0.2064 (q25–q75 0.1171–0.3241)2,206nm — median 0.2066 (q25–q75 0.116–0.3268)2,222nm — median 0.2042 (q25–q75 0.113–0.3211)2,237nm — median 0.195 (q25–q75 0.1087–0.305)2,253nm — median 0.1802 (q25–q75 0.1019–0.2749)2,268nm — median 0.1593 (q25–q75 0.08652–0.2527)2,283nm — median 0.146 (q25–q75 0.07813–0.2506)2,299nm — median 0.1282 (q25–q75 0.07019–0.2367)2,314nm — median 0.1172 (q25–q75 0.06463–0.2255)2,330nm — median 0.1319 (q25–q75 0.0718–0.2351)2,345nm — median 0.1265 (q25–q75 0.06785–0.232)2,361nm — median 0.1261 (q25–q75 0.0692–0.2359)2,376nm — median 0.1291 (q25–q75 0.07189–0.2443)2,392nm — median 0.1327 (q25–q75 0.07322–0.2442)2,407nm — median 0.1351 (q25–q75 0.07406–0.2422)2,423nm — median 0.1373 (q25–q75 0.07532–0.2384)2,438nm — median 0.1333 (q25–q75 0.07508–0.2291)2,454nm — median 0.1314 (q25–q75 0.07519–0.2223)2,469nm — median 0.1341 (q25–q75 0.07597–0.2157)2,485nm — median 0.1357 (q25–q75 0.07991–0.2113)2,500nm — median 0.1418 (q25–q75 0.08177–0.2164)

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.
2,151
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
350–2,500 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.
718

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.
0.00749 – 0.876
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
0.106 – 0.297
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
0.2411
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
518.5
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
0.1909
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
1.6032e-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.
1.5e+04
Roughness S/N proxy dB
?20 log10 of the roughness signal-to-noise proxy. Units are decibels; compare only compatible signal representations.
8e+01 dB
Dynamic range
?Maximum minus minimum of the mean spectrum. Its magnitude depends on the signal representation.
0.191
Smoothness
?Mean per-spectrum RMS of second differences, in signal units. Smaller values indicate smoother spectra under this protocol.
0.0008609
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.
456

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.
70,458
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
4.57%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
50,311
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
3.26%
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.
-0.014118
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.00079716
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.00088309
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
0.12107
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
0.30923
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.15635
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.304
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
0.20748
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
1.2982
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
0.088955
Xcorr lag p95
?95th percentile of the absolute cross-correlation shift relative to the mean spectrum, in spectral channels.
50

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.
11
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.
6.5
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.
2.5
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.
1.5
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.
5
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		0.241130.24weakToo 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		518.510.24weakNormalProbe 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		0.190870.00weakStrong 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		0.0274240.00weakNormal 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		1.6032e-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		150410.00weakGood 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		30.0170.16weakReliable 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		70,4581.00strongArtifactsCosmic 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		4.57%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		50,3111.00strongDetector 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		3.26%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		0.000129%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		-0.0141180.12weakStableIlluminationlinear 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		0.000797160.33weakSmoothBackground, 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		0.000883090.07weakFlatBiology 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		10.8351.00strongAtypical 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		6.4620.81strongExtreme 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		2.5420.64mediumGlobal 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		0.309231.00strongDifferent 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		0.3040.87strongDifferent 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		2.36761.00strongSubpopulationsDifferent 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		3.79371.00strongIsolated 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		0.602421.00strongAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source ASD FieldSpec 4 Hi-Res: 718 of 718 source observations are plotted. PC1 captures 90.6% and PC2 5.9% of the reported spectral variance: 96.6% together; 3.4% 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.

ASD FieldSpec 4 Hi-Res PCA score plot-20-100102030-10-50510PC1 -1.973 · PC2 -2.114PC1 -4.976 · PC2 -1.361PC1 -2.704 · PC2 0.5757PC1 -0.7486 · PC2 0.3742PC1 -1.669 · PC2 -2.714PC1 -0.5539 · PC2 -3.544PC1 0.2464 · PC2 -4.183PC1 0.4984 · PC2 -4.148PC1 -9.386 · PC2 -0.4635PC1 -8.009 · PC2 -0.5511PC1 -2.035 · PC2 -1.829PC1 -6.489 · PC2 -1.181PC1 -7.415 · PC2 -0.7283PC1 -6.611 · PC2 -0.8754PC1 4.252 · PC2 -3.904PC1 4.687 · PC2 -3.835PC1 -7.82 · PC2 -0.106PC1 -6.867 · PC2 -0.2869PC1 9.066 · PC2 0.4586PC1 0.1472 · PC2 -0.06834PC1 5.697 · PC2 0.4068PC1 6.558 · PC2 0.4167PC1 -2.237 · PC2 -1.162PC1 -1.764 · PC2 -1.17PC1 -4.086 · PC2 -1.964PC1 -4.499 · PC2 -1.998PC1 -9.391 · PC2 -0.1955PC1 -8.945 · PC2 -0.1178PC1 3.085 · PC2 -3.134PC1 3.633 · PC2 -3.237PC1 -2.618 · PC2 -1.086PC1 -2.669 · PC2 -0.9167PC1 6.148 · PC2 -0.8084PC1 9.02 · PC2 -1.403PC1 11.51 · PC2 0.09858PC1 12.14 · PC2 0.1565PC1 2.75 · PC2 -0.9258PC1 6.609 · PC2 -0.9104PC1 19.74 · PC2 2.327PC1 20.86 · PC2 1.925PC1 -9.325 · PC2 0.04797PC1 -8.716 · PC2 0.1073PC1 -6.308 · PC2 -1.839PC1 -5.027 · PC2 -2.777PC1 2.973 · PC2 -1.483PC1 2.895 · PC2 -1.497PC1 0.5663 · PC2 -0.4159PC1 2.927 · PC2 -0.3808PC1 6.661 · PC2 -0.5507PC1 12.39 · PC2 0.4299PC1 10.29 · PC2 -0.7467PC1 2.237 · PC2 -0.6664PC1 4.874 · PC2 0.6125PC1 3.964 · PC2 0.2576PC1 3.401 · PC2 -3.776PC1 2.392 · PC2 -3.152PC1 5.181 · PC2 -0.8267PC1 7.397 · PC2 -0.9337PC1 0.8989 · PC2 -2.962PC1 0.1476 · PC2 -2.808PC1 7.093 · PC2 -1.004PC1 7.102 · PC2 -1.103PC1 8.364 · PC2 -0.6064PC1 7.497 · PC2 -0.7819PC1 5.595 · PC2 -1.885PC1 6.648 · PC2 -1.985PC1 2.394 · PC2 -1.952PC1 1.428 · PC2 -1.832PC1 -4.994 · PC2 -0.7958PC1 -4.231 · PC2 -0.8724PC1 4.913 · PC2 -1.999PC1 1.525 · PC2 -1.367PC1 3.037 · PC2 -1.473PC1 1.131 · PC2 -1.466PC1 8.269 · PC2 -1.091PC1 4.303 · PC2 -0.6284PC1 6.407 · PC2 -0.9329PC1 6.499 · PC2 -1.541PC1 8.586 · PC2 -0.4275PC1 9.29 · PC2 -0.7279PC1 6.223 · PC2 -0.615PC1 6.028 · PC2 -0.6376PC1 4.794 · PC2 -1.87PC1 5.96 · PC2 -1.915PC1 4.349 · PC2 -1.52PC1 3.097 · PC2 -2.054PC1 8.952 · PC2 -0.4847PC1 7.327 · PC2 -0.2747PC1 4.329 · PC2 0.2812PC1 7.168 · PC2 0.07241PC1 7.311 · PC2 -1.501PC1 8.194 · PC2 -1.021PC1 -6.665 · PC2 -0.9807PC1 -6.405 · PC2 -1.082PC1 3.062 · PC2 -2.045PC1 7.322 · PC2 -0.7143PC1 1.515 · PC2 0.05696PC1 8.546 · PC2 -0.49PC1 -4.124 · PC2 -1.938PC1 -3.518 · PC2 -2.091PC1 -6.432 · PC2 -0.7669PC1 -6.519 · PC2 -0.7198PC1 -2.15 · PC2 -0.2806PC1 -2.73 · PC2 -0.3326PC1 -4.062 · PC2 -0.8339PC1 -2.077 · PC2 -1.168PC1 -3.01 · PC2 -0.1955PC1 -1.666 · PC2 -0.06963PC1 -9.203 · PC2 -0.5187PC1 -9.177 · PC2 -0.4887PC1 1.46 · PC2 -1.285PC1 -0.2808 · PC2 -1.184PC1 -6.111 · PC2 -0.8815PC1 -4.431 · PC2 -1.164PC1 -0.7311 · PC2 -1.671PC1 0.0274 · PC2 -2.015PC1 8.979 · PC2 2.342PC1 6.293 · PC2 1.067PC1 4.414 · PC2 0.4392PC1 5.159 · PC2 0.2542PC1 6.977 · PC2 3.469PC1 6.619 · PC2 3.772PC1 -0.9991 · PC2 1.867PC1 0.3597 · PC2 1.405PC1 3.676 · PC2 1.632PC1 3.128 · PC2 1.475PC1 1.198 · PC2 2.07PC1 1.033 · PC2 2.262PC1 -0.2398 · PC2 1.615PC1 -0.6182 · PC2 1.566PC1 -9.33 · PC2 0.03469PC1 -9.532 · PC2 0.009166PC1 -9.689 · PC2 -0.06867PC1 -7.366 · PC2 -0.1026PC1 -7.345 · PC2 0.1697PC1 -7.358 · PC2 0.2215PC1 -8.729 · PC2 -0.002194PC1 2.334 · PC2 2.468PC1 -8.282 · PC2 -0.05103PC1 -8.81 · PC2 -0.0558PC1 -7.712 · PC2 -0.4415PC1 -8.277 · PC2 -0.5549PC1 -5.255 · PC2 0.3256PC1 -3.876 · PC2 0.942PC1 -8.613 · PC2 -0.09585PC1 -2.738 · PC2 1.327PC1 -9.702 · PC2 -0.3295PC1 -9.62 · PC2 -0.3329PC1 -9.767 · PC2 -0.1933PC1 -9.758 · PC2 -0.2035PC1 -9.239 · PC2 -0.07787PC1 -9.641 · PC2 0.006256PC1 -8.91 · PC2 0.082PC1 1.932 · PC2 2.268PC1 -5.413 · PC2 -0.4837PC1 -5.811 · PC2 -0.9552PC1 -4.242 · PC2 -0.03628PC1 -6.391 · PC2 0.2392PC1 -9.077 · PC2 0.009961PC1 -0.7652 · PC2 1.677PC1 3.011 · PC2 -0.3478PC1 1.699 · PC2 -0.1479PC1 3.453 · PC2 -1.145PC1 0.8698 · PC2 -0.2722PC1 -4.475 · PC2 0.8414PC1 -8.436 · PC2 -0.2788PC1 2.99 · PC2 0.8431PC1 2.862 · PC2 1.371PC1 -0.6166 · PC2 1.162PC1 -0.3889 · PC2 1.533PC1 4.992 · PC2 2.29PC1 6.446 · PC2 3.015PC1 5.055 · PC2 1.56PC1 4.753 · PC2 1.13PC1 -5.054 · PC2 0.1286PC1 -5.104 · PC2 0.1544PC1 -0.2669 · PC2 -0.3336PC1 -2.845 · PC2 -0.1037PC1 1.625 · PC2 0.8721PC1 5.067 · PC2 1.086PC1 4.489 · PC2 0.2436PC1 5.877 · PC2 0.1019PC1 -1.773 · PC2 1.724PC1 -2.096 · PC2 1.869PC1 -5.869 · PC2 0.9339PC1 -4.186 · PC2 1.621PC1 -0.8309 · PC2 0.3588PC1 -1.395 · PC2 0.5125PC1 -4.451 · PC2 -0.0536PC1 -4.58 · PC2 0.1973PC1 -0.199 · PC2 1.597PC1 0.2661 · PC2 2.453PC1 -2.568 · PC2 0.2122PC1 -3.227 · PC2 0.5526PC1 -4.261 · PC2 0.5892PC1 -5.033 · PC2 0.6608PC1 -0.4547 · PC2 0.4338PC1 -1.265 · PC2 0.4511PC1 -5.385 · PC2 0.3422PC1 -5.582 · PC2 0.2211PC1 2.235 · PC2 2.834PC1 4.222 · PC2 3.434PC1 0.128 · PC2 2.735PC1 3.146 · PC2 3.391PC1 -1.715 · PC2 1.861PC1 -2.669 · PC2 1.416PC1 -9.747 · PC2 -0.2544PC1 -9.47 · PC2 -0.2135PC1 -2.414 · PC2 2.532PC1 -2.773 · PC2 2.618PC1 -4.119 · PC2 1.368PC1 -5.882 · PC2 1.229PC1 0.2918 · PC2 3.065PC1 -0.197 · PC2 2.978PC1 -5.94 · PC2 0.7834PC1 -7.548 · PC2 0.4105PC1 -1.99 · PC2 1.223PC1 -0.9842 · PC2 0.894PC1 -6.673 · PC2 -0.4722PC1 -2.87 · PC2 -1.084PC1 5.864 · PC2 1.357PC1 7.724 · PC2 1.355PC1 3.043 · PC2 0.5684PC1 3.68 · PC2 0.6572PC1 -7.022 · PC2 -0.6963PC1 -9.031 · PC2 -0.0179PC1 -0.5493 · PC2 0.3117PC1 -3.695 · PC2 0.5497PC1 -1.598 · PC2 0.4315PC1 -0.7744 · PC2 0.484PC1 -4.082 · PC2 0.1018PC1 -5.038 · PC2 0.03962PC1 -4.458 · PC2 0.6156PC1 -4.682 · PC2 0.5731PC1 -9.654 · PC2 -0.09968PC1 -9.863 · PC2 -0.08668PC1 23.58 · PC2 1.035PC1 16.81 · PC2 -1.593PC1 7.568 · PC2 -0.8334PC1 6.069 · PC2 -1.223PC1 -7.674 · PC2 -0.6368PC1 -7.917 · PC2 -0.5519PC1 12.39 · PC2 1.641PC1 11.79 · PC2 1.969PC1 5.613 · PC2 -1.338PC1 1.551 · PC2 -0.9737PC1 5.706 · PC2 0.7438PC1 2.378 · PC2 -1.046PC1 4.934 · PC2 -1.251PC1 12.41 · PC2 -2.981PC1 -1.557 · PC2 -1.055PC1 -3.648 · PC2 -0.7282PC1 -1.765 · PC2 -1.304PC1 -2.586 · PC2 -1.086PC1 -1.975 · PC2 -1.276PC1 -1.679 · PC2 -1.803PC1 -9.485 · PC2 -0.1704PC1 -9.331 · PC2 -0.1391PC1 18.93 · PC2 4.436PC1 14.35 · PC2 3.039PC1 -2.944 · PC2 -0.797PC1 -4.803 · PC2 -0.6091PC1 2.425 · PC2 -0.9915PC1 0.6951 · PC2 -0.8776PC1 -7.022 · PC2 -0.3891PC1 -6.906 · PC2 -0.2873PC1 2.67 · PC2 -1.666PC1 2.981 · PC2 -1.499PC1 17.44 · PC2 -1.056PC1 12.03 · PC2 -2.318PC1 -3.799 · PC2 -0.6243PC1 -4.979 · PC2 -0.3561PC1 -8.8 · PC2 -0.2453PC1 -8.517 · PC2 -0.2607PC1 -9.669 · PC2 -0.1016PC1 -7.186 · PC2 -0.1888PC1 4.338 · PC2 -2.597PC1 3.623 · PC2 -1.307PC1 -9.578 · PC2 -0.01924PC1 -9.513 · PC2 0.00139PC1 -1.681 · PC2 -0.7378PC1 -0.9531 · PC2 -0.7476PC1 6.335 · PC2 -1.558PC1 14.7 · PC2 -1.329PC1 -10.04 · PC2 -0.07874PC1 -9.89 · PC2 -0.06977PC1 -1.922 · PC2 -1.255PC1 -2.127 · PC2 -1.517PC1 17.16 · PC2 -0.9709PC1 19.82 · PC2 -1.597PC1 11.97 · PC2 -1.928PC1 14.41 · PC2 -1.472PC1 24.23 · PC2 -0.00343PC1 22.86 · PC2 2.855PC1 5.61 · PC2 -1.837PC1 7.78 · PC2 -1.532PC1 2.982 · PC2 -1.415PC1 1.062 · PC2 -0.8992PC1 -1.413 · PC2 -1.355PC1 -3.373 · PC2 -1.036PC1 8.604 · PC2 -0.9326PC1 9.564 · PC2 -0.9239PC1 2.125 · PC2 -0.4824PC1 4.424 · PC2 -0.599PC1 -8.558 · PC2 -0.3458PC1 -8.456 · PC2 -0.1436PC1 -9.381 · PC2 -0.3388PC1 -8.92 · PC2 -0.3995PC1 -0.3071 · PC2 -1.207PC1 0.4908 · PC2 -1.458PC1 1.388 · PC2 -1.167PC1 -2.461 · PC2 -0.7225PC1 1.506 · PC2 -1.439PC1 -0.5527 · PC2 -0.9609PC1 0.6293 · PC2 -0.4169PC1 0.7714 · PC2 -0.3592PC1 -3.824 · PC2 -0.8921PC1 -6.205 · PC2 -0.672PC1 0.5432 · PC2 -0.7234PC1 -0.5903 · PC2 -0.6785PC1 0.2266 · PC2 -1.291PC1 2.791 · PC2 -1.566PC1 15.03 · PC2 -1.586PC1 18.8 · PC2 1.049PC1 -10.05 · PC2 -0.1353PC1 -9.949 · PC2 -0.1227PC1 3.977 · PC2 -0.4688PC1 6.42 · PC2 -0.5366PC1 1.953 · PC2 -0.7904PC1 -4.771 · PC2 -0.524PC1 3.14 · PC2 -1.772PC1 2.31 · PC2 -1.707PC1 2.432 · PC2 -1.219PC1 -0.9542 · PC2 -0.9929PC1 -2.97 · PC2 -0.8384PC1 0.2952 · PC2 -1.378PC1 -0.1699 · PC2 -1.42PC1 0.5159 · PC2 -1.526PC1 3.657 · PC2 -0.5293PC1 6.415 · PC2 -0.7842PC1 9.626 · PC2 -1.842PC1 15.89 · PC2 -2.153PC1 3.401 · PC2 -0.7138PC1 9.96 · PC2 -1.765PC1 8.061 · PC2 -2.153PC1 15.78 · PC2 -3.539PC1 12.35 · PC2 -0.6463PC1 16.26 · PC2 -1.204PC1 5.838 · PC2 -1.741PC1 13.5 · PC2 -2.965PC1 -7.718 · PC2 -0.8482PC1 -6.092 · PC2 -1.501PC1 -2.999 · PC2 -0.6115PC1 4.708 · PC2 -1.578PC1 11.47 · PC2 -1.538PC1 8.846 · PC2 -1.41PC1 8.918 · PC2 -2.499PC1 11.98 · PC2 -2.499PC1 15.3 · PC2 4.939PC1 10.63 · PC2 2.694PC1 18.36 · PC2 -1.951PC1 20.48 · PC2 0.6882PC1 3.561 · PC2 -1.98PC1 9.415 · PC2 -1.598PC1 12.07 · PC2 -1.716PC1 6.621 · PC2 -2.025PC1 -0.4785 · PC2 0.335PC1 -2.637 · PC2 -0.07254PC1 7.394 · PC2 0.03782PC1 11.16 · PC2 6.429PC1 5.639 · PC2 0.2404PC1 6.167 · PC2 0.3543PC1 6.723 · PC2 -2.239PC1 -3.911 · PC2 0.7114PC1 -1.477 · PC2 1.71PC1 -0.5434 · PC2 1.91PC1 -2.391 · PC2 -0.604PC1 -3.058 · PC2 -1.339PC1 -2.226 · PC2 -1.574PC1 -1.33 · PC2 -1.828PC1 -5.941 · PC2 -0.6466PC1 -7.625 · PC2 -0.334PC1 -7.805 · PC2 -0.393PC1 -6.281 · PC2 -0.5981PC1 -7.635 · PC2 -0.6836PC1 -7.004 · PC2 -0.5331PC1 -8.488 · PC2 -0.367PC1 -8.429 · PC2 -0.4249PC1 -4.134 · PC2 -1.674PC1 -4.457 · PC2 -1.531PC1 8.24 · PC2 -2.296PC1 -1.86 · PC2 0.9513PC1 16.54 · PC2 2.692PC1 4.097 · PC2 1.416PC1 9.812 · PC2 -2.381PC1 9.886 · PC2 -2.448PC1 7.051 · PC2 -2.426PC1 4.48 · PC2 -2.272PC1 2.266 · PC2 -1.428PC1 1.96 · PC2 -1.794PC1 2.75 · PC2 0.5278PC1 2.234 · PC2 0.02182PC1 -2.032 · PC2 -1.979PC1 -2.983 · PC2 -1.804PC1 3.499 · PC2 -1.504PC1 0.207 · PC2 -1.059PC1 -3.583 · PC2 0.0235PC1 -2.967 · PC2 -0.7808PC1 2.368 · PC2 -1.83PC1 2.198 · PC2 -1.543PC1 -1.79 · PC2 -0.8851PC1 -2.962 · PC2 -1.295PC1 2.41 · PC2 0.2901PC1 1.001 · PC2 0.5164PC1 3.335 · PC2 -1.093PC1 -0.9474 · PC2 1.249PC1 10.8 · PC2 -0.7239PC1 7.066 · PC2 -0.7753PC1 -0.9898 · PC2 -1.975PC1 -1.627 · PC2 -1.794PC1 -3.069 · PC2 -1.415PC1 -5.071 · PC2 -1.691PC1 5.441 · PC2 -0.1772PC1 4.688 · PC2 -1.077PC1 -1.966 · PC2 -0.4769PC1 -1.575 · PC2 -1.259PC1 7.077 · PC2 0.2444PC1 4.228 · PC2 -0.1789PC1 0.8692 · PC2 -0.9462PC1 0.424 · PC2 -1.181PC1 -0.1615 · PC2 -1.823PC1 -1.16 · PC2 -1.771PC1 -0.701 · PC2 -0.0982PC1 2.394 · PC2 2.747PC1 -0.7254 · PC2 -1.484PC1 -3.326 · PC2 -1.126PC1 8.226 · PC2 0.1069PC1 4.777 · PC2 -1.518PC1 1.495 · PC2 -0.5723PC1 0.02189 · PC2 -0.7528PC1 -0.9152 · PC2 -1.028PC1 -2.146 · PC2 -1.306PC1 1.085 · PC2 -0.6064PC1 -3.085 · PC2 -0.3555PC1 0.2846 · PC2 -0.638PC1 0.7053 · PC2 1.366PC1 -0.1074 · PC2 0.02004PC1 -1.376 · PC2 -0.218PC1 -3.624 · PC2 -0.4455PC1 -3.19 · PC2 -0.4663PC1 -2.168 · PC2 -1.048PC1 -2.467 · PC2 -1.803PC1 -0.6522 · PC2 -0.7308PC1 0.534 · PC2 0.5583PC1 -2.669 · PC2 -1.179PC1 -2.316 · PC2 -1.158PC1 -3.777 · PC2 -1.146PC1 -3.532 · PC2 -1.104PC1 -1.907 · PC2 -0.8006PC1 -1.881 · PC2 -0.8189PC1 -0.5498 · PC2 -1.524PC1 -0.672 · PC2 -1.764PC1 1.089 · PC2 -2.273PC1 -0.4085 · PC2 -1.948PC1 -3.348 · PC2 -1.185PC1 -2.239 · PC2 -1.357PC1 -6.785 · PC2 -0.5924PC1 -5.991 · PC2 -0.901PC1 -4.878 · PC2 -1.203PC1 -4.21 · PC2 -1.495PC1 -1.959 · PC2 -1.044PC1 -2.936 · PC2 -0.9617PC1 -6.473 · PC2 -1.166PC1 -6.457 · PC2 -1.144PC1 -5.834 · PC2 -1.032PC1 -5.455 · PC2 -1.19PC1 -4.46 · PC2 0.655PC1 -4.072 · PC2 0.8647PC1 2.226 · PC2 3.109PC1 3.344 · PC2 5.087PC1 13.15 · PC2 5.511PC1 8.837 · PC2 7.682PC1 -2.893 · PC2 1.919PC1 -2.616 · PC2 2.023PC1 -4.071 · PC2 3.832PC1 -2.665 · PC2 4.424PC1 -5.259 · PC2 1.646PC1 -5.794 · PC2 1.79PC1 -4.395 · PC2 3.293PC1 -1.356 · PC2 2.813PC1 10.16 · PC2 0.3698PC1 5.901 · PC2 1.489PC1 3.509 · PC2 3.056PC1 6.785 · PC2 6.61PC1 5.438 · PC2 4.65PC1 4.747 · PC2 4.041PC1 -7.205 · PC2 0.152PC1 -7.759 · PC2 0.1793PC1 -6.774 · PC2 0.3246PC1 -6.99 · PC2 0.4122PC1 2.53 · PC2 1.442PC1 3.647 · PC2 1.034PC1 -6.587 · PC2 1.652PC1 -3.994 · PC2 1.994PC1 -5.08 · PC2 -0.4972PC1 -5.811 · PC2 -0.4646PC1 -4.456 · PC2 0.8116PC1 -4.383 · PC2 0.8482PC1 11.92 · PC2 -0.02117PC1 13.96 · PC2 3.881PC1 0.4861 · PC2 2.331PC1 0.002889 · PC2 2.587PC1 3.192 · PC2 -0.422PC1 7.124 · PC2 -2.82PC1 -1.567 · PC2 3.121PC1 -1.811 · PC2 1.701PC1 0.8461 · PC2 2.742PC1 0.2197 · PC2 2.789PC1 -2.147 · PC2 2.064PC1 -8.028 · PC2 -0.661PC1 -2.092 · PC2 1.575PC1 -1.776 · PC2 1.451PC1 2.113 · PC2 0.5709PC1 2.506 · PC2 0.1176PC1 10.62 · PC2 4.339PC1 8.802 · PC2 3.577PC1 -3.527 · PC2 1.756PC1 -3.449 · PC2 1.817PC1 -1.812 · PC2 2.45PC1 -3.303 · PC2 2.649PC1 -9.156 · PC2 0.06193PC1 2.29 · PC2 7.611PC1 9.947 · PC2 1.666PC1 11.32 · PC2 2.495PC1 4.904 · PC2 2.817PC1 5.93 · PC2 2.927PC1 9.245 · PC2 1.834PC1 12.6 · PC2 -2.049PC1 -1.88 · PC2 0.5416PC1 -0.5409 · PC2 0.4771PC1 -6.027 · PC2 -0.1029PC1 -6.077 · PC2 -0.1322PC1 -5.577 · PC2 -0.8175PC1 -6.298 · PC2 0.06977PC1 -8.058 · PC2 -0.1236PC1 -9.424 · PC2 0.0006576PC1 6.487 · PC2 2.299PC1 4.708 · PC2 2.234PC1 -3.14 · PC2 5.883PC1 1.702 · PC2 6.231PC1 -1.794 · PC2 -0.2762PC1 -4.908 · PC2 -0.01662PC1 12.67 · PC2 4.917PC1 8.539 · PC2 3.518PC1 -9.917 · PC2 0.03322PC1 -9.532 · PC2 0.02062PC1 2.533 · PC2 0.7188PC1 4.299 · PC2 1.507PC1 2.529 · PC2 1.965PC1 -2.972 · PC2 1.447PC1 -3.153 · PC2 -0.8045PC1 -0.2544 · PC2 -0.9775PC1 -2.152 · PC2 -0.1364PC1 -1.646 · PC2 -0.2136PC1 1.507 · PC2 1.8PC1 1.472 · PC2 1.325PC1 -5.612 · PC2 1.002PC1 -4.82 · PC2 1.103PC1 -6.907 · PC2 0.2343PC1 -7.314 · PC2 0.1744PC1 -6.203 · PC2 0.1832PC1 -5.749 · PC2 0.2559PC1 -5.35 · PC2 1.516PC1 -5.809 · PC2 1.524PC1 3.521 · PC2 2.312PC1 5.563 · PC2 2.121PC1 -6.018 · PC2 1.111PC1 -3.873 · PC2 1.491PC1 -6.714 · PC2 1.424PC1 -4.586 · PC2 0.4707PC1 3.703 · PC2 4.02PC1 5.488 · PC2 4.605PC1 -5.462 · PC2 0.7166PC1 -4.173 · PC2 0.7677PC1 -1.363 · PC2 0.6523PC1 -1.657 · PC2 0.6657PC1 -2.289 · PC2 0.6245PC1 3.855 · PC2 0.57PC1 -3.708 · PC2 0.5028PC1 -3.913 · PC2 0.3574PC1 0.7873 · PC2 2.008PC1 -1.481 · PC2 1.566PC1 -8.749 · PC2 0.1166PC1 -8.232 · PC2 0.1396PC1 -8.065 · PC2 -0.2604PC1 -8.953 · PC2 -0.1858PC1 1.936 · PC2 0.5029PC1 3.306 · PC2 -0.8323PC1 13.84 · PC2 2.308PC1 14.49 · PC2 2.372PC1 13.71 · PC2 -4.314PC1 14.53 · PC2 -4.323PC1 6.631 · PC2 -3.094PC1 8.059 · PC2 -3.137PC1 16.73 · PC2 -0.6693PC1 12.41 · PC2 -0.8085PC1 -2.068 · PC2 4.45PC1 -3.451 · PC2 4.15PC1 17.16 · PC2 -3.382PC1 15.1 · PC2 -4.214PC1 -8.923 · PC2 0.1439PC1 -6.619 · PC2 -0.3236PC1 10.68 · PC2 -4.168PC1 16.58 · PC2 -4.151PC1 18.46 · PC2 -2.826PC1 20.83 · PC2 -3.08PC1 -7.421 · PC2 0.9695PC1 -7.337 · PC2 1.259PC1 17.84 · PC2 -3.681PC1 13.27 · PC2 -3.129PC1 -9.082 · PC2 0.07764PC1 -8.956 · PC2 0.1254PC1 5.619 · PC2 2.677PC1 5.093 · PC2 3.204PC1 -8.377 · PC2 0.4649PC1 -7.325 · PC2 0.7132PC1 -5.763 · PC2 -0.6858PC1 1.518 · PC2 6.249PC1 -2.253 · PC2 -0.2963PC1 -1.951 · PC2 -0.5703PC1 -9.67 · PC2 -0.1208PC1 -9.634 · PC2 -0.09572PC1 -9.339 · PC2 -0.2552PC1 -4.252 · PC2 0.8699PC1 -9.91 · PC2 0.185PC1 -9.98 · PC2 0.09937PC1 -5.628 · PC2 2.374PC1 -5.553 · PC2 2.484PC1 -9.044 · PC2 -0.1821PC1 -9.389 · PC2 -0.1196PC1 -8.788 · PC2 0.4632PC1 -8.978 · PC2 0.5354PC1 -7.735 · PC2 -0.1166PC1 -7.131 · PC2 -0.005736PC1 -9.846 · PC2 -0.1069PC1 -9.869 · PC2 -0.1139PC1 -8.133 · PC2 0.3418PC1 -8.618 · PC2 0.5688PC1 -8.67 · PC2 0.3136PC1 -8.069 · PC2 -0.123PC1 -8.14 · PC2 0.5001PC1 -7.964 · PC2 0.4575PC1 -6.695 · PC2 -0.08266PC1 -6.135 · PC2 -0.3672PC1 -6.762 · PC2 -0.5706PC1 -6.316 · PC2 -0.6063PC1 -9.63 · PC2 -0.175PC1 -9.435 · PC2 -0.2059PC1 -5.627 · PC2 -0.102PC1 -4.518 · PC2 -0.2648PC1 -9.454 · PC2 -0.03946PC1 -8.43 · PC2 0.02232PC1 -7.391 · PC2 0.5756PC1 -7.525 · PC2 0.4478PC1 -9.698 · PC2 -0.2563PC1 -9.985 · PC2 -0.1859PC1 -9.53 · PC2 -0.1158PC1 -9.483 · PC2 -0.07866PC1 0.8799 · PC2 -3.073PC1 2.009 · PC2 -3.719PC1 -1.106 · PC2 -0.7301PC1 0.7184 · PC2 -1.145PC1 -5.812 · PC2 0.4186PC1 -7.496 · PC2 0.3031PC1 -8.926 · PC2 0.4967PC1 -8.962 · PC2 0.3487PC1 -9.583 · PC2 -0.1919PC1 -7.47 · PC2 -0.3457PC1 -6.821 · PC2 -0.2814PC1 -7.573 · PC2 -0.07006PC1 -10.03 · PC2 -0.1344PC1 -9.874 · PC2 -0.1026PC1 -7.52 · PC2 0.3259PC1 -8.115 · PC2 0.04145PC1 -9.475 · PC2 0.1239PC1 -9.509 · PC2 0.08958PC1 4.824 · PC2 4.756PC1 8.912 · PC2 5.834PC1 11.08 · PC2 3.397PC1 9.355 · PC2 2.445PC1 3.209 · PC2 2.566PC1 5.381 · PC2 2.526PC1 1.921 · PC2 -0.348PC1 -2.321 · PC2 -0.04738PC1 -7.459 · PC2 -0.3039PC1 -8.278 · PC2 -0.1854PC1 0.768 · PC2 0.2396PC1 -0.5341 · PC2 -1.17PC1 2.583 · PC2 3.906PC1 -0.2707 · PC2 3.353PC1 -0.2108 · PC2 2.859PC1 -0.3164 · PC2 2.975PC1 -4.264 · PC2 0.8646PC1 -4.657 · PC2 1.178PC1 -4.24 · PC2 1.655PC1 -4.189 · PC2 2.613PC1 2.186 · PC2 -1.979PC1 2.575 · PC2 -1.842PC1 3.312 · PC2 3.872PC1 8.283 · PC2 4.517PC1 -8.026 · PC2 0.04269PC1 -9.463 · PC2 -0.03661PC1 5.843 · PC2 -4.465PC1 -3.561 · PC2 0.2516PC1 16 · PC2 4.686PC1 11.27 · PC2 3.834PC1 13.44 · PC2 -5.381PC1 9.139 · PC2 0.9291PC1 (90.6%)PC2 (5.9%)718 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
1-1.9729-2.1139
2-4.9756-1.3614
3-2.70430.57565
4-0.748550.37422
5-1.6686-2.7137
6-0.55393-3.5442
70.24644-4.1831
80.4984-4.1482
9-9.3864-0.46347
10-8.0094-0.55109
11-2.0355-1.8287
12-6.4894-1.181
13-7.4152-0.72832
14-6.6111-0.87544
154.2521-3.9042
164.6868-3.8352
17-7.8196-0.10598
18-6.8669-0.28695
199.06570.45863
200.14723-0.068345
215.69720.40684
226.55840.41675
23-2.2365-1.1616
24-1.7644-1.1696
25-4.0863-1.9636
26-4.4987-1.9985
27-9.3913-0.19555
28-8.9449-0.11784
293.0853-3.1344
303.6329-3.2369
31-2.6179-1.086
32-2.6687-0.91675
336.1478-0.80841
349.0202-1.4029
3511.5150.09858
3612.1370.15646
372.7505-0.92584
386.6088-0.91041
3919.7382.3267
4020.8571.9247
41-9.32540.047968
42-8.71650.10735
43-6.3083-1.8387
44-5.0269-2.7771
452.9726-1.4834
462.8954-1.4967
470.56632-0.41591
482.9271-0.38083
496.6609-0.55075
5012.390.42989
5110.287-0.74671
522.2366-0.66638
534.87410.61252
543.96430.2576
553.4012-3.7762
562.3923-3.1516
575.1811-0.82672
587.3969-0.93373
590.89895-2.9622
600.14763-2.8084
617.0934-1.0037
627.1023-1.1027
638.3637-0.6064
647.4971-0.78194
655.595-1.8846
666.6483-1.9847
672.3938-1.9521
681.4277-1.8319
69-4.9941-0.79582
70-4.2309-0.87235
714.9129-1.9994
721.5248-1.3671
733.0372-1.4733
741.1311-1.4657
758.2692-1.0905
764.3027-0.62841
776.4074-0.93287
786.4991-1.5409
798.5856-0.4275
809.2901-0.72787
816.2229-0.61505
826.0276-0.63756
834.7935-1.8702
845.9604-1.9155
854.3487-1.5201
863.0972-2.0536
878.9525-0.48473
887.3271-0.27468
894.32860.2812
907.16780.072411
917.3109-1.5007
928.1941-1.0214
93-6.6652-0.98069
94-6.4049-1.0817
953.0617-2.0455
967.3225-0.71428
971.51520.056961
988.5459-0.48996
99-4.1242-1.9385
100-3.5184-2.0908
101-6.4316-0.76691
102-6.5189-0.71985
103-2.1499-0.28056
104-2.7301-0.33258
105-4.0617-0.8339
106-2.0774-1.1681
107-3.0097-0.19552
108-1.6665-0.069635
109-9.2026-0.51866
110-9.177-0.48874
1111.4597-1.285
112-0.28078-1.1844
113-6.1112-0.88149
114-4.4313-1.1643
115-0.73114-1.6707
1160.027398-2.0152
1178.97922.3419
1186.29351.0667
1194.41430.43916
1205.15910.2542
1216.97733.4688
1226.61873.7718
123-0.999121.8667
1240.359721.4053
1253.67581.6319
1263.12811.475
1271.19782.07
1281.03282.2625
129-0.239821.615
130-0.618231.5665
131-9.33010.03469
132-9.53240.0091658
133-9.6887-0.068666
134-7.3661-0.1026
135-7.3450.16974
136-7.35780.2215
137-8.729-0.0021938
1382.33372.4676
139-8.2819-0.051034
140-8.8096-0.055801
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7189.13870.92911

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: 90.6% (cumulative 90.6%)1PC2: 5.9% (cumulative 96.6%)2PC3: 1.5% (cumulative 98.1%)3PC4: 0.7% (cumulative 98.8%)4PC5: 0.4% (cumulative 99.2%)5PC6: 0.2% (cumulative 99.4%)6PC7: 0.2% (cumulative 99.6%)7PC8: 0.1% (cumulative 99.7%)8PC9: 0.1% (cumulative 99.7%)9PC10: 0.1% (cumulative 99.8%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
View explained variance values
Variance per displayed principal component
ComponentSpectral variance
PC190.62%
PC25.93%
PC31.55%
PC40.68%
PC50.44%
PC60.22%
PC70.15%
PC80.07%
PC90.07%
PC100.06%

Viavi microNIR

X_micronir · NIR · Viavi microNIR

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.

Viavi microNIR spectra0.00.20.40.60.81.08001,0001,2001,4001,6001,800q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm908.1nm — median 0.4146 (q25–q75 0.328–0.5531)914.29nm — median 0.4203 (q25–q75 0.3299–0.5688)920.49nm — median 0.4242 (q25–q75 0.3298–0.5859)926.68nm — median 0.431 (q25–q75 0.3305–0.5994)932.88nm — median 0.436 (q25–q75 0.3297–0.6063)939.07nm — median 0.4388 (q25–q75 0.3309–0.6145)945.27nm — median 0.4416 (q25–q75 0.3309–0.6214)951.46nm — median 0.444 (q25–q75 0.33–0.6286)957.65nm — median 0.4453 (q25–q75 0.3303–0.634)963.85nm — median 0.4468 (q25–q75 0.3301–0.6396)970.04nm — median 0.4477 (q25–q75 0.3296–0.643)976.24nm — median 0.448 (q25–q75 0.3291–0.6454)982.43nm — median 0.4471 (q25–q75 0.3279–0.6467)988.63nm — median 0.4465 (q25–q75 0.327–0.6475)994.82nm — median 0.4461 (q25–q75 0.3265–0.648)1001nm — median 0.4455 (q25–q75 0.3256–0.648)1007.2nm — median 0.4444 (q25–q75 0.3241–0.6475)1013.4nm — median 0.4445 (q25–q75 0.3226–0.6468)1019.6nm — median 0.4442 (q25–q75 0.321–0.6465)1025.8nm — median 0.4438 (q25–q75 0.3199–0.6455)1032nm — median 0.4435 (q25–q75 0.3189–0.644)1038.2nm — median 0.4427 (q25–q75 0.3181–0.6415)1044.4nm — median 0.4418 (q25–q75 0.3174–0.64)1050.6nm — median 0.441 (q25–q75 0.3177–0.6396)1056.8nm — median 0.4408 (q25–q75 0.3171–0.6372)1063nm — median 0.441 (q25–q75 0.3169–0.637)1069.2nm — median 0.4416 (q25–q75 0.3164–0.6367)1075.3nm — median 0.4416 (q25–q75 0.316–0.6369)1081.5nm — median 0.4417 (q25–q75 0.3156–0.6372)1087.7nm — median 0.4416 (q25–q75 0.3158–0.6383)1093.9nm — median 0.4414 (q25–q75 0.3156–0.6388)1100.1nm — median 0.4413 (q25–q75 0.3158–0.6401)1106.3nm — median 0.4415 (q25–q75 0.3162–0.6414)1112.5nm — median 0.4416 (q25–q75 0.3166–0.6427)1118.7nm — median 0.4435 (q25–q75 0.3168–0.6435)1124.9nm — median 0.4442 (q25–q75 0.318–0.6456)1131.1nm — median 0.4441 (q25–q75 0.3192–0.6485)1137.3nm — median 0.4432 (q25–q75 0.3199–0.6509)1143.5nm — median 0.4437 (q25–q75 0.3208–0.6533)1149.7nm — median 0.4442 (q25–q75 0.3225–0.6555)1155.9nm — median 0.4461 (q25–q75 0.3273–0.6584)1162.1nm — median 0.4503 (q25–q75 0.3307–0.6619)1168.3nm — median 0.4537 (q25–q75 0.3329–0.6615)1174.5nm — median 0.4553 (q25–q75 0.3344–0.6664)1180.7nm — median 0.4581 (q25–q75 0.3372–0.6677)1186.8nm — median 0.4588 (q25–q75 0.3395–0.6688)1193nm — median 0.461 (q25–q75 0.3446–0.6681)1199.2nm — median 0.467 (q25–q75 0.3477–0.6694)1205.4nm — median 0.4713 (q25–q75 0.3521–0.6715)1211.6nm — median 0.4774 (q25–q75 0.3537–0.6725)1217.8nm — median 0.4756 (q25–q75 0.3521–0.6702)1224nm — median 0.4663 (q25–q75 0.3444–0.6663)1230.2nm — median 0.4546 (q25–q75 0.3377–0.6584)1236.4nm — median 0.4514 (q25–q75 0.3341–0.6493)1242.6nm — median 0.4487 (q25–q75 0.3305–0.6465)1248.8nm — median 0.4469 (q25–q75 0.3267–0.6439)1255nm — median 0.4454 (q25–q75 0.3243–0.6423)1261.2nm — median 0.4446 (q25–q75 0.3235–0.6412)1267.4nm — median 0.444 (q25–q75 0.3233–0.6407)1273.6nm — median 0.4432 (q25–q75 0.3232–0.6404)1279.8nm — median 0.4426 (q25–q75 0.3231–0.64)1286nm — median 0.4423 (q25–q75 0.3224–0.6396)1292.2nm — median 0.4421 (q25–q75 0.3219–0.6391)1298.3nm — median 0.4418 (q25–q75 0.3216–0.6387)1304.5nm — median 0.4416 (q25–q75 0.3215–0.6384)1310.7nm — median 0.4413 (q25–q75 0.3216–0.638)1316.9nm — median 0.4412 (q25–q75 0.3218–0.6373)1323.1nm — median 0.4412 (q25–q75 0.3227–0.6388)1329.3nm — median 0.4412 (q25–q75 0.3227–0.6396)1335.5nm — median 0.441 (q25–q75 0.3231–0.6396)1341.7nm — median 0.4417 (q25–q75 0.3243–0.6399)1347.9nm — median 0.4426 (q25–q75 0.326–0.6403)1354.1nm — median 0.444 (q25–q75 0.3276–0.6403)1360.3nm — median 0.4457 (q25–q75 0.3306–0.6415)1366.5nm — median 0.4463 (q25–q75 0.3332–0.6443)1372.7nm — median 0.4477 (q25–q75 0.3357–0.6485)1378.9nm — median 0.4501 (q25–q75 0.3386–0.6528)1385.1nm — median 0.4542 (q25–q75 0.3409–0.6598)1391.3nm — median 0.4565 (q25–q75 0.3441–0.6637)1397.5nm — median 0.4567 (q25–q75 0.3447–0.6663)1403.6nm — median 0.4579 (q25–q75 0.3439–0.6651)1409.8nm — median 0.4617 (q25–q75 0.3453–0.6586)1416nm — median 0.4647 (q25–q75 0.3489–0.6545)1422.2nm — median 0.4649 (q25–q75 0.3526–0.6545)1428.4nm — median 0.4668 (q25–q75 0.3541–0.6561)1434.6nm — median 0.4675 (q25–q75 0.3541–0.6544)1440.8nm — median 0.4696 (q25–q75 0.3528–0.6516)1447nm — median 0.4696 (q25–q75 0.3511–0.6496)1453.2nm — median 0.4697 (q25–q75 0.3493–0.6489)1459.4nm — median 0.4693 (q25–q75 0.3497–0.6457)1465.6nm — median 0.4683 (q25–q75 0.3494–0.6447)1471.8nm — median 0.4677 (q25–q75 0.3485–0.644)1478nm — median 0.4661 (q25–q75 0.3475–0.6429)1484.2nm — median 0.4651 (q25–q75 0.3467–0.6416)1490.4nm — median 0.4644 (q25–q75 0.3473–0.6422)1496.6nm — median 0.4637 (q25–q75 0.3476–0.6503)1502.8nm — median 0.4638 (q25–q75 0.3476–0.6506)1509nm — median 0.4633 (q25–q75 0.3489–0.6517)1515.1nm — median 0.4639 (q25–q75 0.3489–0.6509)1521.3nm — median 0.4637 (q25–q75 0.3492–0.6496)1527.5nm — median 0.4639 (q25–q75 0.3497–0.649)1533.7nm — median 0.4641 (q25–q75 0.3501–0.6484)1539.9nm — median 0.4647 (q25–q75 0.3502–0.6482)1546.1nm — median 0.4657 (q25–q75 0.3508–0.6493)1552.3nm — median 0.4664 (q25–q75 0.3516–0.6498)1558.5nm — median 0.4661 (q25–q75 0.3533–0.65)1564.7nm — median 0.466 (q25–q75 0.3542–0.6502)1570.9nm — median 0.4665 (q25–q75 0.3551–0.6503)1577.1nm — median 0.4674 (q25–q75 0.3561–0.6505)1583.3nm — median 0.4683 (q25–q75 0.357–0.6506)1589.5nm — median 0.4691 (q25–q75 0.3581–0.6503)1595.7nm — median 0.4696 (q25–q75 0.3587–0.6503)1601.9nm — median 0.4705 (q25–q75 0.3596–0.6534)1608.1nm — median 0.4721 (q25–q75 0.3594–0.6557)1614.3nm — median 0.4739 (q25–q75 0.361–0.6552)1620.5nm — median 0.474 (q25–q75 0.3605–0.6568)1626.6nm — median 0.4732 (q25–q75 0.361–0.6627)1632.8nm — median 0.4744 (q25–q75 0.3639–0.6671)1639nm — median 0.4735 (q25–q75 0.3671–0.6701)1645.2nm — median 0.4741 (q25–q75 0.3696–0.6692)1651.4nm — median 0.4745 (q25–q75 0.3721–0.6681)1657.6nm — median 0.4767 (q25–q75 0.3739–0.6682)1663.8nm — median 0.4774 (q25–q75 0.378–0.6689)1670nm — median 0.4778 (q25–q75 0.3818–0.6688)1676.2nm — median 0.477 (q25–q75 0.3831–0.6701)

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.
125
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
908.1–1676 nm
Mean spacing
?Average difference between adjacent spectral-axis coordinates; compare only within the same unit.
6.19 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.
720

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.
-0.0761 – 1.04
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
0.442 – 0.525
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
0.5002
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
384.3
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
0.08293
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
0.00021483
Roughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR.
2.3e+03
Roughness S/N proxy dB
?20 log10 of the roughness signal-to-noise proxy. Units are decibels; compare only compatible signal representations.
7e+01 dB
Dynamic range
?Maximum minus minimum of the mean spectrum. Its magnitude depends on the signal representation.
0.0829
Smoothness
?Mean per-spectrum RMS of second differences, in signal units. Smaller values indicate smoother spectra under this protocol.
0.001246
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.
399

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.
1,125
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
1.27%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
1,971
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
2.21%
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.
0.034128
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.0010192
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.003156
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
0.16146
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
0.39374
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.03777
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.18349
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
1.0418
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
1.8636
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
0.048439
Xcorr lag p95
?95th percentile of the absolute cross-correlation shift relative to the mean spectrum, in spectral channels.
2

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.
11
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.
6.2
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.
2.5
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.
1.1
PCs → 95% var
?Number of principal components needed to explain 95% of spectral variance, when reached by the computed projection.
1
PCs → 99% var
?Number of principal components needed to explain 99% of spectral variance, when reached by the computed projection.
2
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		0.50020.30weakToo 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		384.310.30weakNormalProbe 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		0.0829270.00weakStrong 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		0.0473150.00weakNormal 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		0.000214830.01weakStableLamp, 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		2328.50.00weakGood 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		690.080.00weakReliable 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		1,1251.00strongArtifactsCosmic 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		1.27%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		1,9711.00strongDetector 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		2.21%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		0.00222%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		0.0341280.14weakStableIlluminationlinear 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		0.00101920.20weakSmoothBackground, 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		0.0031560.13weakFlatBiology 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		10.5351.00strongAtypical 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		6.23550.78strongExtreme 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		2.49710.62mediumGlobal 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		0.393741.00strongDifferent 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		0.183490.52mediumDifferent 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		42.0071.00strongSubpopulationsDifferent 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		3.47811.00strongIsolated 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		0.594711.00strongAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source Viavi microNIR: 720 of 720 source observations are plotted. PC1 captures 98.4% and PC2 1.2% of the reported spectral variance: 99.6% together; 0.4% 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.

Viavi microNIR PCA score plot-50510-2-10123PC1 -1.464 · PC2 -0.005146PC1 -2.488 · PC2 -0.2053PC1 0.07058 · PC2 -0.1498PC1 -1.45 · PC2 0.3724PC1 -1.745 · PC2 0.1595PC1 -2.627 · PC2 -0.2512PC1 -0.4256 · PC2 0.04143PC1 -0.574 · PC2 0.1583PC1 1.023 · PC2 -0.04247PC1 1.172 · PC2 0.1499PC1 -0.72 · PC2 -0.1942PC1 -2.618 · PC2 0.07347PC1 -3.439 · PC2 0.1894PC1 -1.381 · PC2 0.2302PC1 1.503 · PC2 -0.198PC1 3.895 · PC2 0.1222PC1 -3.824 · PC2 0.2666PC1 1.908 · PC2 -0.02973PC1 0.6726 · PC2 -0.3158PC1 -2.433 · PC2 -0.01201PC1 0.192 · PC2 -0.05035PC1 2.512 · PC2 -0.01772PC1 0.1735 · PC2 -0.1962PC1 -1.76 · PC2 -0.149PC1 -3.338 · PC2 0.1114PC1 0.5728 · PC2 0.2458PC1 -3.98 · PC2 -0.124PC1 4.596 · PC2 0.1777PC1 -1.757 · PC2 -0.0425PC1 -1.462 · PC2 -0.002241PC1 0.484 · PC2 -0.3846PC1 -2.177 · PC2 -0.2007PC1 -0.6483 · PC2 0.2198PC1 -0.1411 · PC2 0.09463PC1 -1.765 · PC2 -0.1421PC1 -0.3736 · PC2 -0.4658PC1 -0.4172 · PC2 0.1635PC1 -2.77 · PC2 -0.1231PC1 0.6113 · PC2 2.058PC1 -0.3243 · PC2 -0.05187PC1 -3.635 · PC2 -0.2129PC1 -1.779 · PC2 0.2412PC1 -2.832 · PC2 0.1051PC1 3.11 · PC2 0.06982PC1 1.347 · PC2 0.0893PC1 -1.375 · PC2 0.121PC1 -1.613 · PC2 -0.04717PC1 -4.173 · PC2 0.1021PC1 -2.653 · PC2 -0.1507PC1 -1.857 · PC2 0.05176PC1 4.119 · PC2 0.01494PC1 -0.7218 · PC2 -0.1585PC1 -3.557 · PC2 -0.2463PC1 2.803 · PC2 -0.07062PC1 -4.773 · PC2 -0.2214PC1 1.202 · PC2 -0.08243PC1 -0.3925 · PC2 0.2926PC1 0.1051 · PC2 0.8477PC1 -3.601 · PC2 0.05254PC1 -0.9604 · PC2 -0.03263PC1 -2.944 · PC2 -0.1958PC1 -2.629 · PC2 -0.09269PC1 -1.351 · PC2 0.04698PC1 -0.7424 · PC2 -0.003555PC1 -1.183 · PC2 -0.004038PC1 -2.96 · PC2 0.01099PC1 4.951 · PC2 0.2413PC1 -2.251 · PC2 0.4309PC1 1.189 · PC2 0.06122PC1 3.901 · PC2 0.2689PC1 4.659 · PC2 0.1671PC1 4.058 · PC2 -0.003307PC1 -0.8862 · PC2 0.5013PC1 -0.3128 · PC2 0.3043PC1 -3.123 · PC2 0.2702PC1 1.025 · PC2 0.07566PC1 3.528 · PC2 0.1248PC1 3.276 · PC2 0.0424PC1 -1.152 · PC2 0.1577PC1 5.155 · PC2 0.1127PC1 1.175 · PC2 0.2284PC1 4.138 · PC2 0.02849PC1 3.935 · PC2 -0.1354PC1 4.355 · PC2 0.09073PC1 4.281 · PC2 -0.07221PC1 1.825 · PC2 0.07788PC1 -1.115 · PC2 0.2961PC1 0.8408 · PC2 -0.01921PC1 3.637 · PC2 -0.236PC1 1.244 · PC2 -0.05138PC1 3.811 · PC2 -0.1155PC1 4.64 · PC2 0.1315PC1 3.034 · PC2 0.185PC1 2.479 · PC2 0.01221PC1 -0.1924 · PC2 -0.07478PC1 1.904 · PC2 0.03899PC1 3.364 · PC2 -0.09291PC1 0.9959 · PC2 0.0805PC1 1.573 · PC2 -0.06189PC1 0.1491 · PC2 -0.036PC1 3.927 · PC2 -0.0698PC1 -0.8526 · PC2 -0.05244PC1 3.144 · PC2 -0.3783PC1 0.9232 · PC2 0.1851PC1 3.829 · PC2 -0.04101PC1 3.487 · PC2 -0.3816PC1 5.329 · PC2 0.1568PC1 -2.158 · PC2 -0.3158PC1 -1.336 · PC2 -0.05432PC1 4.215 · PC2 0.009646PC1 3.174 · PC2 0.1158PC1 3.924 · PC2 0.1732PC1 3.893 · PC2 0.1429PC1 5.232 · PC2 -0.3182PC1 0.2991 · PC2 0.1412PC1 3.069 · PC2 -0.04563PC1 0.4218 · PC2 0.3588PC1 5.54 · PC2 0.1134PC1 2.097 · PC2 -0.1028PC1 4.369 · PC2 -0.1519PC1 3.792 · PC2 -0.1162PC1 2.807 · PC2 -0.09591PC1 3.713 · PC2 -0.22PC1 0.5404 · PC2 -0.055PC1 -2.91 · PC2 0.1863PC1 -2.63 · PC2 0.00459PC1 -2.546 · PC2 -0.01054PC1 -2.924 · PC2 0.1603PC1 0.07316 · PC2 0.01069PC1 3.719 · PC2 0.1318PC1 0.7687 · PC2 0.03568PC1 -1.131 · PC2 0.06876PC1 -2.072 · PC2 0.0743PC1 2.111 · PC2 0.4163PC1 -0.4408 · PC2 -0.0113PC1 -3.225 · PC2 0.2663PC1 2.85 · PC2 0.01759PC1 3.872 · PC2 -0.1909PC1 -1.72 · PC2 0.001243PC1 -0.1229 · PC2 0.1018PC1 4.301 · PC2 0.002187PC1 -1.722 · PC2 -0.1559PC1 1.306 · PC2 -0.07774PC1 0.4573 · PC2 0.3948PC1 2.646 · PC2 0.1173PC1 0.3808 · PC2 0.1474PC1 4.109 · PC2 0.09615PC1 -1.518 · PC2 0.2726PC1 0.4647 · PC2 0.1249PC1 -1.834 · PC2 -0.5021PC1 -1.448 · PC2 0.4992PC1 -2.511 · PC2 0.3502PC1 0.6129 · PC2 0.162PC1 3.766 · PC2 -0.03638PC1 -2.195 · PC2 0.03576PC1 1.135 · PC2 -0.06991PC1 -3.326 · PC2 0.3538PC1 -1.452 · PC2 0.3467PC1 -3.033 · PC2 0.2016PC1 0.7003 · PC2 0.07772PC1 -0.2227 · PC2 -0.1671PC1 0.1404 · PC2 -0.07883PC1 -1.459 · PC2 0.3094PC1 0.04619 · PC2 0.05343PC1 -2.478 · PC2 0.1222PC1 -1.083 · PC2 0.2474PC1 -1.451 · PC2 0.02147PC1 -1.422 · PC2 0.5897PC1 -1.135 · PC2 -0.03609PC1 -0.4929 · PC2 0.1058PC1 -1.949 · PC2 0.1786PC1 -1.34 · PC2 0.1347PC1 -1.843 · PC2 0.3089PC1 1.755 · PC2 0.01387PC1 0.854 · PC2 0.4974PC1 -0.03684 · PC2 -0.1999PC1 -1.505 · PC2 0.2602PC1 1.24 · PC2 0.2603PC1 -2.472 · PC2 0.2304PC1 -1.396 · PC2 0.2164PC1 -2.05 · PC2 0.06962PC1 0.1719 · PC2 0.04945PC1 1.556 · PC2 0.05193PC1 0.9872 · PC2 0.3427PC1 -1.941 · PC2 0.0131PC1 -1.379 · PC2 0.1099PC1 -0.364 · PC2 0.01337PC1 1.906 · PC2 -0.07775PC1 -0.3923 · PC2 0.3106PC1 -1.54 · PC2 0.05192PC1 1.961 · PC2 -0.05942PC1 0.7583 · PC2 -0.09985PC1 -0.6895 · PC2 -0.1333PC1 -1.115 · PC2 -0.07199PC1 4.052 · PC2 0.06761PC1 2.882 · PC2 0.1102PC1 2.586 · PC2 0.1566PC1 -1.847 · PC2 0.05862PC1 3.888 · PC2 0.126PC1 -1.331 · PC2 -0.09411PC1 -3.032 · PC2 -0.1549PC1 1.296 · PC2 0.9977PC1 -0.6072 · PC2 -0.0742PC1 0.7737 · PC2 0.006048PC1 4.605 · PC2 0.08558PC1 -2.909 · PC2 0.1991PC1 4.136 · PC2 0.1634PC1 -0.9189 · PC2 0.03748PC1 3.149 · PC2 0.09769PC1 -1.664 · PC2 0.1132PC1 -1.335 · PC2 0.1146PC1 -1.634 · PC2 0.01816PC1 -0.211 · PC2 -0.05526PC1 3.141 · PC2 0.1428PC1 -1.35 · PC2 -0.3121PC1 -1.727 · PC2 -0.2504PC1 -1.977 · PC2 0.08505PC1 -1.461 · PC2 -0.1425PC1 -1.206 · PC2 -0.01734PC1 0.5845 · PC2 0.02429PC1 -0.2523 · PC2 -0.00923PC1 -2.888 · PC2 -0.1418PC1 1.063 · PC2 -0.1596PC1 3.518 · PC2 -0.05548PC1 4.414 · PC2 0.1909PC1 -0.3962 · PC2 0.0198PC1 -1.845 · PC2 0.07942PC1 5.03 · PC2 0.05645PC1 0.7455 · PC2 -0.1546PC1 1.745 · PC2 -0.1062PC1 -0.6327 · PC2 0.05238PC1 -2.021 · PC2 0.05374PC1 -1.874 · PC2 0.004063PC1 0.2867 · PC2 0.06142PC1 0.7978 · PC2 -0.04885PC1 -2.545 · PC2 -0.06611PC1 0.8905 · PC2 -0.1806PC1 2.819 · PC2 -0.0453PC1 4.308 · PC2 0.1426PC1 -0.7734 · PC2 -0.1708PC1 -2.468 · PC2 -0.1491PC1 1.729 · PC2 -0.1816PC1 -1.815 · PC2 0.1156PC1 -2.301 · PC2 0.1917PC1 -1.57 · PC2 -0.05291PC1 -0.2918 · PC2 0.03663PC1 -0.2335 · PC2 -0.0336PC1 1.433 · PC2 -0.1004PC1 0.5842 · PC2 -0.08616PC1 -2.02 · PC2 0.1176PC1 -1.71 · PC2 -0.0327PC1 -0.5813 · PC2 -0.08099PC1 0.1508 · PC2 -0.162PC1 -2.424 · PC2 0.1736PC1 -2.238 · PC2 0.2827PC1 -3.541 · PC2 -0.1152PC1 -3.869 · PC2 -0.1461PC1 0.06397 · PC2 -0.1258PC1 -1.859 · PC2 0.2631PC1 -2.612 · PC2 -0.08298PC1 4.377 · PC2 0.01106PC1 -3.37 · PC2 0.2464PC1 3.808 · PC2 0.1046PC1 0.4881 · PC2 -0.6776PC1 -1.811 · PC2 0.05203PC1 -1.884 · PC2 -0.1403PC1 -2.053 · PC2 -0.01239PC1 -2.975 · PC2 0.03864PC1 -2.305 · PC2 0.3036PC1 -1.201 · PC2 -0.03746PC1 -1.478 · PC2 -0.01443PC1 1.041 · PC2 -0.1218PC1 -2.2 · PC2 0.1377PC1 -2.307 · PC2 -0.1291PC1 -1.399 · PC2 0.07872PC1 -0.7067 · PC2 0.02126PC1 2.449 · PC2 -0.2416PC1 -1.424 · PC2 0.07625PC1 -0.4963 · PC2 0.05271PC1 -1.86 · PC2 -0.05025PC1 0.5552 · PC2 -0.06318PC1 -0.6889 · PC2 0.2534PC1 -2.404 · PC2 0.1638PC1 -4.469 · PC2 -0.05028PC1 -2.198 · PC2 -0.1263PC1 -1.01 · PC2 0.0353PC1 -0.9178 · PC2 -0.111PC1 1.413 · PC2 -0.1041PC1 -1.731 · PC2 -1.205PC1 -1.526 · PC2 -1.209PC1 -1.897 · PC2 -1.178PC1 -2.757 · PC2 -0.8136PC1 3.224 · PC2 -0.737PC1 -1.09 · PC2 -0.8356PC1 3.072 · PC2 -0.7894PC1 0.341 · PC2 -0.9475PC1 -1.881 · PC2 -0.9133PC1 -2.36 · PC2 -0.4197PC1 -1.396 · PC2 -0.2485PC1 -0.5026 · PC2 -0.4064PC1 -1.412 · PC2 -0.3238PC1 -1.793 · PC2 0.1727PC1 0.1289 · PC2 -0.123PC1 0.6941 · PC2 -0.1576PC1 -1.266 · PC2 0.04287PC1 -1.443 · PC2 -0.1483PC1 -1.086 · PC2 -0.1088PC1 -3.7 · PC2 -0.1157PC1 4.117 · PC2 0.01426PC1 -0.9926 · PC2 -0.05597PC1 -0.8948 · PC2 0.004197PC1 -0.02909 · PC2 -0.19PC1 -0.8007 · PC2 -0.05426PC1 -2.009 · PC2 -0.1274PC1 -1.064 · PC2 -0.07441PC1 -0.5424 · PC2 -0.1371PC1 -0.6077 · PC2 -0.05437PC1 -1.86 · PC2 -0.1595PC1 0.07678 · PC2 -0.0808PC1 0.6176 · PC2 0.009306PC1 -1.057 · PC2 -0.1101PC1 3.027 · PC2 -0.01396PC1 -2.317 · PC2 -0.06915PC1 -0.7463 · PC2 -0.1869PC1 -2.47 · PC2 0.1633PC1 2.952 · PC2 -0.1033PC1 2.62 · PC2 -0.1342PC1 1.246 · PC2 -0.3434PC1 -0.1927 · PC2 -0.06425PC1 1.624 · PC2 -0.2863PC1 -1.134 · PC2 -0.1295PC1 3.76 · PC2 -0.1359PC1 1.599 · PC2 -0.01916PC1 2.106 · PC2 -0.1647PC1 3.938 · PC2 -0.2452PC1 0.1128 · PC2 -0.01955PC1 5.541 · PC2 -0.1156PC1 4.11 · PC2 -0.1384PC1 0.3859 · PC2 -0.1456PC1 4.545 · PC2 0.00851PC1 -0.007788 · PC2 -0.2006PC1 2.459 · PC2 0.04082PC1 1.375 · PC2 0.1475PC1 -1.478 · PC2 -0.1117PC1 2.289 · PC2 0.08853PC1 5.397 · PC2 -0.04362PC1 3.125 · PC2 -0.1504PC1 2.977 · PC2 -0.1627PC1 1.165 · PC2 0.05661PC1 0.82 · PC2 -0.2859PC1 3.599 · PC2 -0.1371PC1 2.37 · PC2 -0.1692PC1 -2.503 · PC2 0.1217PC1 -1.544 · PC2 -0.0006856PC1 3.794 · PC2 0.03414PC1 -1.574 · PC2 0.001211PC1 -1.452 · PC2 0.1455PC1 0.3105 · PC2 -0.1572PC1 0.3652 · PC2 -0.2226PC1 3.092 · PC2 -0.244PC1 -2.153 · PC2 0.02498PC1 -1.991 · PC2 -0.1301PC1 0.389 · PC2 -0.2147PC1 -1.666 · PC2 0.4467PC1 -2.004 · PC2 0.3076PC1 -3.456 · PC2 -0.2686PC1 -0.3447 · PC2 0.04627PC1 -1.801 · PC2 0.1925PC1 0.7763 · PC2 -0.05448PC1 1.143 · PC2 0.1636PC1 -1.278 · PC2 -0.1248PC1 -1.747 · PC2 -0.005714PC1 -3.21 · PC2 0.2116PC1 -1.871 · PC2 0.2148PC1 1.78 · PC2 -0.1924PC1 5.019 · PC2 0.1736PC1 -3.979 · PC2 0.3683PC1 2.09 · PC2 0.02195PC1 0.7428 · PC2 -0.33PC1 -2.415 · PC2 0.004795PC1 0.4636 · PC2 -0.031PC1 2.433 · PC2 0.006542PC1 0.2057 · PC2 -0.2124PC1 -2.709 · PC2 0.02861PC1 -3.922 · PC2 0.1182PC1 1.204 · PC2 0.1718PC1 -4.137 · PC2 -0.1531PC1 4.512 · PC2 0.1642PC1 -2.56 · PC2 -0.157PC1 -1.683 · PC2 0.07676PC1 0.05905 · PC2 -0.09956PC1 -2.299 · PC2 -0.2929PC1 -0.8555 · PC2 0.2078PC1 -0.1227 · PC2 0.0866PC1 -3.399 · PC2 -0.1892PC1 -2.765 · PC2 -0.3119PC1 -0.5671 · PC2 0.1544PC1 -2.992 · PC2 -0.1322PC1 0.8173 · PC2 1.978PC1 -0.2061 · PC2 0.04135PC1 -3.947 · PC2 -0.2678PC1 -2.23 · PC2 0.1813PC1 -2.696 · PC2 0.1248PC1 3.434 · PC2 0.0698PC1 1.036 · PC2 0.06424PC1 -1.213 · PC2 0.07464PC1 -2.433 · PC2 -0.0639PC1 -4.259 · PC2 0.1034PC1 -2.591 · PC2 -0.168PC1 -1.724 · PC2 0.06377PC1 3.764 · PC2 0.06154PC1 -2.095 · PC2 -0.2114PC1 -4.194 · PC2 -0.2108PC1 4.042 · PC2 -0.005018PC1 -4.659 · PC2 -0.2203PC1 1.51 · PC2 -0.09652PC1 0.1521 · PC2 0.3748PC1 0.9146 · PC2 0.8571PC1 -4.359 · PC2 0.1357PC1 -0.7353 · PC2 -0.08815PC1 -3.992 · PC2 -0.2153PC1 -2.45 · PC2 -0.1406PC1 -1.411 · PC2 0.04926PC1 -0.3128 · PC2 -0.09286PC1 -2.711 · PC2 0.01905PC1 -2.028 · PC2 -0.01509PC1 4.906 · PC2 0.2257PC1 -2.118 · PC2 0.5202PC1 1.025 · PC2 0.1069PC1 3.702 · PC2 0.2264PC1 3.374 · PC2 -0.1037PC1 2.132 · PC2 0.5202PC1 -3.852 · PC2 0.7163PC1 -2.622 · PC2 0.3629PC1 0.4104 · PC2 0.2814PC1 0.8551 · PC2 0.09479PC1 4.437 · PC2 0.1782PC1 3.839 · PC2 -0.07515PC1 -1.245 · PC2 0.2188PC1 4.349 · PC2 0.1028PC1 0.4066 · PC2 0.3782PC1 -1.164 · PC2 0.2763PC1 2.789 · PC2 -0.02688PC1 5.241 · PC2 0.1244PC1 3.683 · PC2 0.02862PC1 2.594 · PC2 0.005423PC1 -0.6454 · PC2 0.3448PC1 -0.3445 · PC2 -0.06114PC1 4.4 · PC2 0.06521PC1 0.5398 · PC2 -0.08663PC1 -1.328 · PC2 0.5104PC1 3.506 · PC2 0.09022PC1 2.47 · PC2 -0.07227PC1 4.461 · PC2 0.01164PC1 2.101 · PC2 0.1059PC1 1.622 · PC2 0.0375PC1 3.867 · PC2 -0.03931PC1 1.931 · PC2 -0.0603PC1 0.4709 · PC2 -0.2206PC1 -0.6907 · PC2 -0.2152PC1 4.053 · PC2 -0.07309PC1 -0.1261 · PC2 -0.1406PC1 2.778 · PC2 -0.2745PC1 1.084 · PC2 0.1725PC1 4.747 · PC2 -0.1305PC1 4.432 · PC2 -0.09765PC1 4.6 · PC2 0.1586PC1 -0.2338 · PC2 -0.2235PC1 -2.237 · PC2 -0.04358PC1 4.205 · PC2 -0.03076PC1 2.543 · PC2 0.02613PC1 3.641 · PC2 0.18PC1 3.177 · PC2 0.2311PC1 3.858 · PC2 -0.2433PC1 2.502 · PC2 0.02956PC1 1.119 · PC2 -0.001057PC1 3.868 · PC2 0.136PC1 4.497 · PC2 0.1223PC1 1.564 · PC2 0.05855PC1 3.811 · PC2 -0.24PC1 3.5 · PC2 -0.2031PC1 3.031 · PC2 -0.03533PC1 5.246 · PC2 -0.3231PC1 0.1666 · PC2 -0.1488PC1 -2.715 · PC2 0.1561PC1 -2.896 · PC2 -0.02357PC1 -2.982 · PC2 -0.04465PC1 -1.937 · PC2 0.1024PC1 -0.754 · PC2 -0.02465PC1 3.186 · PC2 0.1108PC1 -2.662 · PC2 0.132PC1 -1.44 · PC2 0.004842PC1 -0.6368 · PC2 -0.05273PC1 -0.1323 · PC2 0.4665PC1 -3.225 · PC2 0.1339PC1 -2.231 · PC2 0.1365PC1 -1.4 · PC2 -0.2359PC1 2.779 · PC2 0.07286PC1 -2.048 · PC2 -0.04396PC1 -2.184 · PC2 0.1007PC1 4.391 · PC2 0.02151PC1 -2.247 · PC2 -0.1231PC1 1.189 · PC2 0.1585PC1 0.2633 · PC2 0.4964PC1 1.363 · PC2 0.1304PC1 -1.542 · PC2 0.2397PC1 4.213 · PC2 0.1402PC1 -1.757 · PC2 0.4025PC1 -0.7269 · PC2 0.08PC1 -3.217 · PC2 -0.2862PC1 -2.176 · PC2 0.4017PC1 -1.623 · PC2 0.1849PC1 0.1947 · PC2 0.5038PC1 -0.7829 · PC2 0.1462PC1 -2.209 · PC2 0.01713PC1 -1.407 · PC2 0.4684PC1 -1.667 · PC2 0.312PC1 -3.018 · PC2 0.6808PC1 -3.494 · PC2 0.1636PC1 0.1677 · PC2 -0.04104PC1 1.145 · PC2 0.03771PC1 -1.169 · PC2 -0.06453PC1 -2.044 · PC2 0.1249PC1 -0.992 · PC2 0.1168PC1 -2.944 · PC2 0.1076PC1 -1.85 · PC2 0.2435PC1 -1.381 · PC2 -0.05844PC1 -3.659 · PC2 0.6539PC1 -0.2217 · PC2 0.007554PC1 -3.446 · PC2 0.3758PC1 -2.267 · PC2 0.196PC1 -1.058 · PC2 0.2964PC1 -3.252 · PC2 0.2946PC1 -0.2317 · PC2 -0.1742PC1 -2.394 · PC2 0.5889PC1 -0.3843 · PC2 -0.1737PC1 -1.59 · PC2 0.235PC1 1.325 · PC2 0.2631PC1 -1.872 · PC2 0.1291PC1 -0.4328 · PC2 0.4596PC1 -1.687 · PC2 0.002271PC1 -0.1417 · PC2 -0.01722PC1 2.48 · PC2 0.3377PC1 0.5191 · PC2 0.3743PC1 -1.892 · PC2 0.01204PC1 -1.845 · PC2 0.08097PC1 -0.7421 · PC2 0.03005PC1 1.365 · PC2 0.006574PC1 0.3423 · PC2 0.05616PC1 -0.9911 · PC2 0.06413PC1 0.9711 · PC2 -0.02966PC1 1.001 · PC2 0.03226PC1 0.7584 · PC2 -0.1774PC1 -0.9456 · PC2 -0.07693PC1 4.072 · PC2 0.1435PC1 2.765 · PC2 0.1001PC1 2.617 · PC2 0.1553PC1 -1.798 · PC2 0.08731PC1 -1.121 · PC2 0.2293PC1 -0.9812 · PC2 -0.105PC1 -4.665 · PC2 -0.1582PC1 -0.585 · PC2 0.7816PC1 -1.108 · PC2 -0.107PC1 0.8959 · PC2 -0.1007PC1 4.173 · PC2 0.06642PC1 -2.987 · PC2 0.2415PC1 4.784 · PC2 0.1368PC1 -1.503 · PC2 0.06837PC1 4.131 · PC2 0.1117PC1 -2.011 · PC2 0.1314PC1 -2.669 · PC2 0.2516PC1 -1.071 · PC2 0.05614PC1 -0.5728 · PC2 -0.08241PC1 3.327 · PC2 0.05162PC1 -1.672 · PC2 -0.4016PC1 -1.321 · PC2 -0.2831PC1 -1.441 · PC2 0.001722PC1 -1.188 · PC2 -0.08622PC1 -1.502 · PC2 0.05963PC1 0.8042 · PC2 0.01395PC1 -0.9542 · PC2 0.05908PC1 -2.654 · PC2 -0.1138PC1 0.7589 · PC2 -0.149PC1 0.697 · PC2 -0.04644PC1 4.476 · PC2 0.1877PC1 0.1015 · PC2 -0.142PC1 -1.821 · PC2 0.09793PC1 3.354 · PC2 -0.2025PC1 -0.5343 · PC2 -0.1038PC1 1.293 · PC2 -0.1572PC1 -0.4339 · PC2 -0.01853PC1 -2.387 · PC2 0.04331PC1 -1.795 · PC2 -0.005442PC1 -1.566 · PC2 0.00969PC1 1.225 · PC2 -0.1292PC1 -2.251 · PC2 -0.07802PC1 0.6852 · PC2 -0.1004PC1 2.353 · PC2 -0.1532PC1 4.325 · PC2 0.1471PC1 -0.7837 · PC2 -0.1006PC1 -2.441 · PC2 -0.1443PC1 1.636 · PC2 -0.1479PC1 -2.331 · PC2 0.07159PC1 -3.18 · PC2 0.1373PC1 -1.102 · PC2 -0.02005PC1 -0.002644 · PC2 -0.04446PC1 -0.2141 · PC2 -0.08522PC1 1.086 · PC2 -0.05727PC1 -1.184 · PC2 0.09531PC1 -2.596 · PC2 0.1406PC1 -2.018 · PC2 -0.05212PC1 -2.054 · PC2 -0.002534PC1 0.3816 · PC2 -0.1039PC1 -2.356 · PC2 0.1149PC1 -2.159 · PC2 0.08259PC1 -3.745 · PC2 -0.1204PC1 -3.478 · PC2 -0.05644PC1 0.05697 · PC2 -0.08636PC1 -2.022 · PC2 0.2442PC1 -1.906 · PC2 -0.1097PC1 4.088 · PC2 -0.1091PC1 -4.004 · PC2 0.2027PC1 3.863 · PC2 -0.1525PC1 0.4464 · PC2 -0.5993PC1 -1.614 · PC2 0.01638PC1 -1.639 · PC2 -0.1619PC1 -2.643 · PC2 0.01655PC1 -3.101 · PC2 0.007939PC1 -2.346 · PC2 0.311PC1 -0.9878 · PC2 0.01828PC1 -2.235 · PC2 -0.06024PC1 -0.1865 · PC2 -0.09077PC1 -1.684 · PC2 0.1169PC1 -1.732 · PC2 -0.1518PC1 -1.346 · PC2 0.06906PC1 -1.339 · PC2 -0.006832PC1 1.926 · PC2 -0.06288PC1 -0.8136 · PC2 0.107PC1 -0.4133 · PC2 -0.0714PC1 1.812 · PC2 0.02783PC1 0.02331 · PC2 -0.04717PC1 -0.7827 · PC2 0.259PC1 -0.9891 · PC2 0.08186PC1 -4.559 · PC2 -0.1243PC1 -2.693 · PC2 -0.1401PC1 -0.7414 · PC2 0.05454PC1 -0.7158 · PC2 -0.07018PC1 1.053 · PC2 0.0511PC1 -1.419 · PC2 -1.159PC1 -3.2 · PC2 -1.328PC1 -2.085 · PC2 -1.205PC1 -2.795 · PC2 -0.7019PC1 3.209 · PC2 -0.7005PC1 -1.326 · PC2 -0.8335PC1 3.234 · PC2 -0.7788PC1 -0.7987 · PC2 -0.899PC1 -1.536 · PC2 -0.8904PC1 -4.053 · PC2 -0.1602PC1 -1.294 · PC2 -0.3002PC1 -1.57 · PC2 -0.2834PC1 -1.844 · PC2 -0.3495PC1 -1.781 · PC2 0.2128PC1 -1.162 · PC2 -0.1282PC1 0.2973 · PC2 -0.1397PC1 -2.955 · PC2 0.1958PC1 -0.5363 · PC2 -0.1589PC1 -1.683 · PC2 -0.1815PC1 -3.569 · PC2 -0.1673PC1 4.563 · PC2 0.1017PC1 -1.481 · PC2 -0.08551PC1 -0.9512 · PC2 -0.01959PC1 -0.119 · PC2 -0.2161PC1 -0.751 · PC2 -0.05109PC1 -1.378 · PC2 -0.04955PC1 -0.4463 · PC2 -0.07065PC1 -0.9076 · PC2 -0.09203PC1 -0.8634 · PC2 -0.106PC1 -2.261 · PC2 -0.1337PC1 0.003293 · PC2 -0.08645PC1 0.7351 · PC2 0.01311PC1 -0.9784 · PC2 -0.09607PC1 3.008 · PC2 -0.03083PC1 -2.636 · PC2 0.03743PC1 -1.771 · PC2 -0.1409PC1 -0.6996 · PC2 0.167PC1 -1.74 · PC2 -0.1455PC1 3.659 · PC2 -0.1476PC1 0.8927 · PC2 -0.3428PC1 -1.432 · PC2 0.1475PC1 1.903 · PC2 -0.1766PC1 -2.595 · PC2 -0.1462PC1 2.248 · PC2 -0.09081PC1 1.278 · PC2 -0.05041PC1 3.155 · PC2 -0.1217PC1 4.169 · PC2 0.01562PC1 2.297 · PC2 0.05143PC1 3.966 · PC2 -0.1979PC1 4.868 · PC2 -0.08235PC1 1.001 · PC2 -0.08003PC1 3.975 · PC2 -0.09606PC1 -1.254 · PC2 -0.09399PC1 1.715 · PC2 0.08965PC1 0.8167 · PC2 0.005499PC1 -1.756 · PC2 -0.07729PC1 3.662 · PC2 0.1431PC1 5.293 · PC2 -0.01273PC1 4.925 · PC2 0.09282PC1 4.251 · PC2 0.01011PC1 1.054 · PC2 0.08195PC1 -0.1966 · PC2 -0.01251PC1 -0.6412 · PC2 -0.1176PC1 0.7705 · PC2 -0.126PC1 -2.462 · PC2 0.1163PC1 -1.629 · PC2 0.01393PC1 2.703 · PC2 -0.02095PC1 -1.254 · PC2 -0.008436PC1 -0.9589 · PC2 0.1317PC1 0.07203 · PC2 -0.08269PC1 -0.6684 · PC2 -0.07846PC1 3.505 · PC2 -0.1038PC1 (98.4%)PC2 (1.2%)720 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
1-1.4641-0.0051458
2-2.4882-0.20534
30.070578-0.14978
4-1.45030.3724
5-1.74510.15955
6-2.6268-0.25124
7-0.425620.041427
8-0.573970.15831
91.0234-0.042466
101.17160.14986
11-0.71997-0.19418
12-2.6180.073475
13-3.43870.18937
14-1.38080.23025
151.5027-0.19797
163.89540.12224
17-3.82380.26656
181.9075-0.029731
190.67262-0.31581
20-2.4325-0.012014
210.19204-0.050355
222.5121-0.01772
230.1735-0.19619
24-1.7597-0.14896
25-3.33820.11139
260.572840.24578
27-3.9799-0.12404
284.59570.17765
29-1.7572-0.042499
30-1.4622-0.0022405
310.48402-0.38462
32-2.1774-0.20068
33-0.64830.21981
34-0.141090.094627
35-1.7653-0.14213
36-0.37359-0.46578
37-0.417190.16354
38-2.7704-0.12309
390.611292.0581
40-0.32432-0.051866
41-3.6348-0.21289
42-1.77910.24124
43-2.83210.10514
443.10970.069816
451.34670.089297
46-1.37520.121
47-1.613-0.047166
48-4.17270.10212
49-2.6525-0.15072
50-1.85690.051756
514.1190.014939
52-0.72182-0.15854
53-3.5571-0.2463
542.8032-0.07062
55-4.7735-0.22138
561.2018-0.08243
57-0.392530.29264
580.105140.84774
59-3.60060.052544
60-0.96035-0.032629
61-2.9435-0.19578
62-2.6289-0.092685
63-1.3510.046984
64-0.74242-0.0035553
65-1.1832-0.0040379
66-2.95990.010995
674.9510.24129
68-2.25080.43087
691.18910.061221
703.90090.26892
714.6590.16713
724.0583-0.0033066
73-0.886150.50135
74-0.312790.30425
75-3.12310.27025
761.02460.075656
773.52810.12483
783.27610.042404
79-1.15210.15768
805.15540.11272
811.1750.22839
824.13770.028485
833.9345-0.13543
844.3550.090732
854.2815-0.072206
861.82540.077877
87-1.1150.29614
880.84078-0.019207
893.637-0.23598
901.2441-0.05138
913.8114-0.11548
924.64030.1315
933.03380.18502
942.47910.01221
95-0.19244-0.074781
961.90390.038995
973.3636-0.092913
980.995880.080497
991.5731-0.061891
1000.14912-0.035998
1013.9271-0.069799
102-0.85256-0.052435
1033.1442-0.37825
1040.92320.18512
1053.8287-0.041007
1063.4875-0.38155
1075.32930.15681
108-2.1583-0.31584
109-1.336-0.054321
1104.21490.0096463
1113.17440.11576
1123.92390.17319
1133.89260.14293
1145.2324-0.31824
1150.299150.14117
1163.0692-0.045628
1170.421750.35876
1185.540.11338
1192.0974-0.10276
1204.3689-0.15191
1213.7925-0.11619
1222.8075-0.095914
1233.7127-0.22
1240.54041-0.054999
125-2.91030.18625
126-2.630.0045903
127-2.5459-0.01054
128-2.92350.16034
1290.0731630.010688
1303.71850.13179
1310.768750.035677
132-1.13150.068765
133-2.07190.074295
1342.1110.41626
135-0.44076-0.011304
136-3.22460.26627
1372.850.017592
1383.8721-0.19088
139-1.72010.0012428
140-0.122890.10179
1414.30060.0021867
142-1.7221-0.15586
1431.3058-0.077736
1440.457290.39483
1452.64590.11733
1460.380770.1474
1474.10870.096153
148-1.51830.27259
1490.464740.12493
150-1.8343-0.50209
151-1.44760.4992
152-2.51060.35022
1530.612930.16201
1543.7656-0.036385
155-2.19520.035756
1561.1352-0.069909
157-3.32640.35383
158-1.45220.34672
159-3.03330.20162
1600.700320.077718
161-0.22274-0.16712
1620.1404-0.078826
163-1.45890.30942
1640.0461930.053434
165-2.4780.12221
166-1.08280.24745
167-1.45070.02147
168-1.42210.58972
169-1.1349-0.036088
170-0.49290.10582
171-1.94890.17855
172-1.34020.13469
173-1.84320.30895
1741.75550.013874
1750.854010.49744
176-0.036844-0.19986
177-1.50490.26018
1781.23950.26027
179-2.47230.23041
180-1.39620.21636
181-2.04970.069625
1820.171890.049451
1831.5560.051929
1840.987180.34269
185-1.94110.013095
186-1.37940.10994
187-0.3640.013373
1881.9064-0.077746
189-0.392340.31059
190-1.53970.05192
1911.9614-0.059422
1920.75826-0.099849
193-0.68953-0.13335
194-1.1146-0.071987
1954.05220.067607
1962.88180.11024
1972.58590.15659
198-1.8470.058616
1993.88830.126
200-1.331-0.09411
201-3.0321-0.15492
2021.29650.99768
203-0.60717-0.074197
2040.773740.0060482
2054.60490.085578
206-2.90850.1991
2074.13570.16337
208-0.918890.037476
2093.14890.097687
210-1.66390.11322
211-1.33460.11458
212-1.63360.018158
213-0.21097-0.055258
2143.1410.14281
215-1.3502-0.31205
216-1.7266-0.2504
217-1.97710.085046
218-1.4611-0.14245
219-1.2065-0.017341
2200.584490.024291
221-0.25227-0.0092304
222-2.8881-0.14179
2231.0632-0.15957
2243.5176-0.055482
2254.41410.19086
226-0.396180.0198
227-1.8450.079418
2285.02970.056448
2290.74552-0.15455
2301.7448-0.10616
231-0.632730.052382
232-2.02080.053737
233-1.87440.0040633
2340.286730.061418
2350.79784-0.048846
236-2.5453-0.066115
2370.89054-0.1806
2382.8186-0.045299
2394.30810.14258
240-0.77344-0.17082
241-2.4682-0.14905
2421.7289-0.18156
243-1.81460.11559
244-2.30150.1917
245-1.5699-0.052912
246-0.291790.036626
247-0.23347-0.033596
2481.4326-0.10036
2490.58424-0.086161
250-2.01990.11756
251-1.7101-0.032701
252-0.5813-0.080992
2530.15084-0.16196
254-2.4240.17359
255-2.23760.28274
256-3.5406-0.11518
257-3.869-0.1461
2580.063974-0.12583
259-1.85910.26315
260-2.6122-0.082979
2614.37710.011062
262-3.36990.2464
2633.80760.10465
2640.48815-0.67758
265-1.81070.052032
266-1.8838-0.14033
267-2.0534-0.012391
268-2.9750.03864
269-2.30530.30357
270-1.201-0.037459
271-1.4779-0.014429
2721.0414-0.12176
273-2.20.13771
274-2.3069-0.12906
275-1.39910.078725
276-0.706660.021256
2772.4492-0.24157
278-1.4240.076252
279-0.496340.052709
280-1.8599-0.050248
2810.55524-0.06318
282-0.688910.25343
283-2.40450.16384
284-4.4694-0.050279
285-2.1982-0.12629
286-1.00970.0353
287-0.91784-0.11097
2881.4135-0.10411
289-1.7311-1.2052
290-1.5257-1.2088
291-1.8969-1.1778
292-2.7568-0.81364
2933.2242-0.73699
294-1.0896-0.8356
2953.0721-0.78941
2960.34099-0.94752
297-1.8809-0.91331
298-2.3599-0.41973
299-1.396-0.24852
300-0.50255-0.4064
301-1.4118-0.32377
302-1.79270.17267
3030.12888-0.12299
3040.69408-0.15759
305-1.26550.042869
306-1.4429-0.14832
307-1.0864-0.10883
308-3.7001-0.11573
3094.11720.014262
310-0.99259-0.055967
311-0.894770.0041969
312-0.029089-0.18997
313-0.80075-0.054263
314-2.009-0.12741
315-1.0635-0.074406
316-0.54243-0.13714
317-0.60771-0.05437
318-1.8599-0.15945
3190.076785-0.0808
3200.617560.0093064
321-1.0571-0.11008
3223.0271-0.013965
323-2.3171-0.069146
324-0.74632-0.18688
325-2.47030.16333
3262.9522-0.10332
3272.6205-0.13418
3281.2461-0.34337
329-0.19272-0.064251
3301.6237-0.28628
331-1.1337-0.12952
3323.7602-0.1359
3331.5986-0.019159
3342.1058-0.16469
3353.9381-0.24521
3360.11284-0.019547
3375.5409-0.11561
3384.1097-0.13837
3390.38594-0.14562
3404.54480.0085102
341-0.0077875-0.20063
3422.45940.040825
3431.37520.14752
344-1.4776-0.11167
3452.28850.088525
3465.3973-0.043616
3473.1248-0.15043
3482.9771-0.16266
3491.16490.056612
3500.82003-0.28586
3513.5995-0.13711
3522.3704-0.1692
353-2.50270.12167
354-1.5444-0.00068559
3553.79410.034136
356-1.57420.0012109
357-1.45190.1455
3580.31049-0.15722
3590.36518-0.22259
3603.0922-0.24399
361-2.15270.024979
362-1.9911-0.13014
3630.38897-0.21475
364-1.66640.44674
365-2.00410.3076
366-3.4557-0.26858
367-0.34470.046273
368-1.80050.19252
3690.77633-0.054482
3701.14290.16359
371-1.2783-0.12478
372-1.7474-0.0057143
373-3.21020.2116
374-1.87070.21479
3751.7801-0.19238
3765.01850.17358
377-3.97910.36826
3782.08970.021948
3790.74279-0.33002
380-2.41530.0047954
3810.46356-0.030995
3822.4330.0065423
3830.20568-0.21239
384-2.7090.028614
385-3.92190.11815
3861.20390.17175
387-4.1366-0.15313
3884.5120.16419
389-2.5604-0.15702
390-1.68320.076757
3910.059049-0.099565
392-2.2991-0.29288
393-0.855450.20784
394-0.122690.086598
395-3.3992-0.1892
396-2.7649-0.31191
397-0.56710.15435
398-2.9925-0.13225
3990.817331.9784
400-0.206060.041348
401-3.9474-0.26783
402-2.22960.1813
403-2.69570.1248
4043.43370.069802
4051.0360.064244
406-1.21260.074642
407-2.4334-0.063905
408-4.25890.10342
409-2.5907-0.16801
410-1.72380.063775
4113.76440.061537
412-2.0946-0.21144
413-4.1938-0.21075
4144.0418-0.0050178
415-4.6587-0.2203
4161.5096-0.096523
4170.15210.37484
4180.914570.85711
419-4.35870.13569
420-0.73533-0.088149
421-3.992-0.21528
422-2.4498-0.14065
423-1.41090.049264
424-0.31275-0.09286
425-2.71070.019051
426-2.0277-0.015094
4274.90630.22567
428-2.11760.52023
4291.02510.10688
4303.7020.22638
4313.3737-0.10367
4322.13180.52015
433-3.8520.71634
434-2.62230.36295
4350.410390.28139
4360.855140.094795
4374.43730.17825
4383.8386-0.075147
439-1.24510.21882
4404.34870.10284
4410.406630.37821
442-1.16430.27633
4432.7888-0.026883
4445.24080.12443
4453.68330.028617
4462.59370.0054233
447-0.645360.34476
448-0.34448-0.061145
4494.40050.065206
4500.53981-0.086632
451-1.32830.51045
4523.50550.090218
4532.4701-0.072265
4544.46050.011641
4552.10090.10588
4561.62220.037501
4573.8674-0.039314
4581.9314-0.060302
4590.47093-0.22063
460-0.69067-0.21518
4614.0529-0.073091
462-0.12608-0.14064
4632.7783-0.27451
4641.08440.17246
4654.7466-0.13049
4664.4323-0.097651
4674.60030.15858
468-0.23385-0.22346
469-2.237-0.043583
4704.205-0.030762
4712.54270.02613
4723.6410.17998
4733.17710.23108
4743.8583-0.24331
4752.50190.029562
4761.1188-0.0010571
4773.8680.136
4784.49650.1223
4791.56360.058547
4803.8112-0.23998
4813.4997-0.20311
4823.0308-0.035331
4835.246-0.32308
4840.1666-0.14877
485-2.71490.15609
486-2.8964-0.023567
487-2.9816-0.044653
488-1.93670.10241
489-0.75402-0.024648
4903.18570.1108
491-2.66160.13198
492-1.44030.0048417
493-0.63677-0.052734
494-0.132260.46653
495-3.22550.1339
496-2.23120.13649
497-1.4003-0.23591
4982.7790.072864
499-2.0477-0.043958
500-2.18420.1007
5014.3910.021507
502-2.2473-0.12309
5031.18920.15846
5040.263260.49635
5051.36320.13041
506-1.54240.23969
5074.21250.14024
508-1.75680.40251
509-0.726890.079998
510-3.2166-0.28623
511-2.17610.40173
512-1.62280.18488
5130.194690.50377
514-0.782910.14624
515-2.2090.017132
516-1.40680.46843
517-1.66740.31196
518-3.01760.68077
519-3.49430.16358
5200.16774-0.041038
5211.14530.03771
522-1.1695-0.064531
523-2.04370.12493
524-0.992040.11676
525-2.94390.10763
526-1.85040.24354
527-1.3806-0.058442
528-3.65860.65387
529-0.221750.0075539
530-3.44570.37581
531-2.26670.19598
532-1.05820.29639
533-3.25230.29461
534-0.2317-0.17421
535-2.39410.58886
536-0.38435-0.17369
537-1.59040.23501
5381.32490.2631
539-1.87180.12909
540-0.432760.45958
541-1.68690.0022708
542-0.14166-0.017216
5432.47990.33768
5440.519120.3743
545-1.89170.01204
546-1.84530.08097
547-0.742060.030052
5481.36460.0065737
5490.342260.05616
550-0.991070.064131
5510.9711-0.02966
5521.00150.032255
5530.75837-0.17736
554-0.94562-0.076931
5554.07190.14346
5562.76520.10011
5572.61730.15533
558-1.79750.087307
559-1.12070.22932
560-0.9812-0.10498
561-4.6649-0.15824
562-0.585010.78158
563-1.1082-0.10698
5640.89593-0.1007
5654.17310.066423
566-2.98710.24147
5674.78350.13677
568-1.50250.068365
5694.13050.11165
570-2.01140.13136
571-2.66880.25162
572-1.07150.056142
573-0.57279-0.082414
5743.32710.051621
575-1.6723-0.40163
576-1.3206-0.2831
577-1.4410.0017222
578-1.1875-0.086224
579-1.50170.059625
5800.804150.013951
581-0.954230.059078
582-2.6544-0.1138
5830.75892-0.14902
5840.697-0.046439
5854.47560.18765
5860.10152-0.14204
587-1.82050.097925
5883.354-0.20253
589-0.53428-0.10375
5901.2932-0.15722
591-0.43387-0.018526
592-2.38650.043314
593-1.795-0.0054418
594-1.56550.0096902
5951.2251-0.12921
596-2.2508-0.078018
5970.68516-0.10042
5982.3534-0.15322
5994.32490.1471
600-0.78374-0.10063
601-2.4409-0.14434
6021.6356-0.14793
603-2.33050.071588
604-3.180.13725
605-1.1018-0.020046
606-0.0026444-0.04446
607-0.21412-0.085218
6081.0856-0.057273
609-1.18440.095305
610-2.5960.14061
611-2.0181-0.052123
612-2.0539-0.0025336
6130.38161-0.10391
614-2.35590.11487
615-2.15890.082593
616-3.7451-0.12036
617-3.4783-0.056439
6180.056971-0.086358
619-2.02190.24421
620-1.9057-0.10967
6214.0877-0.10912
622-4.00390.20266
6233.8626-0.15253
6240.44645-0.59931
625-1.61410.016378
626-1.6393-0.16191
627-2.64280.016552
628-3.10140.0079393
629-2.34650.31097
630-0.987810.018283
631-2.2353-0.060244
632-0.18654-0.090769
633-1.68440.11686
634-1.7317-0.15181
635-1.34560.069064
636-1.3388-0.0068315
6371.9264-0.062877
638-0.813580.10701
639-0.41332-0.071397
6401.81180.027834
6410.023309-0.047173
642-0.78270.25896
643-0.989050.081858
644-4.5593-0.1243
645-2.693-0.14006
646-0.741370.054543
647-0.71583-0.07018
6481.05340.051102
649-1.4189-1.1585
650-3.1995-1.3284
651-2.0852-1.2054
652-2.7952-0.7019
6533.2087-0.7005
654-1.3263-0.83348
6553.2335-0.77878
656-0.79869-0.89898
657-1.5356-0.89035
658-4.053-0.16019
659-1.2945-0.30016
660-1.5702-0.28335
661-1.8441-0.34955
662-1.78130.2128
663-1.1623-0.12823
6640.29727-0.13966
665-2.95540.19582
666-0.53626-0.15886
667-1.6825-0.18147
668-3.5687-0.16732
6694.56280.1017
670-1.4809-0.085506
671-0.95116-0.019588
672-0.11896-0.21612
673-0.75104-0.051088
674-1.3779-0.049549
675-0.44627-0.070651
676-0.90761-0.092034
677-0.86343-0.10597
678-2.2611-0.13366
6790.003293-0.086447
6800.735120.01311
681-0.9784-0.096073
6823.0079-0.030829
683-2.63610.037435
684-1.7707-0.14085
685-0.699580.16695
686-1.7397-0.1455
6873.6593-0.14756
6880.89268-0.34277
689-1.43170.14751
6901.9032-0.17661
691-2.5947-0.1462
6922.2482-0.090806
6931.2777-0.050405
6943.1551-0.12167
6954.16920.015617
6962.29670.051435
6973.9664-0.19788
6984.8684-0.082352
6991.0007-0.080026
7003.9745-0.09606
701-1.2545-0.093993
7021.71490.089651
7030.816740.0054994
704-1.7556-0.077289
7053.66170.14313
7065.2932-0.012731
7074.9250.09282
7084.25130.010106
7091.05430.081951
710-0.19661-0.012515
711-0.64121-0.11759
7120.77054-0.12604
713-2.46160.11627
714-1.62910.013928
7152.703-0.020948
716-1.2538-0.0084362
717-0.958870.13166
7180.072033-0.082687
719-0.66838-0.078461
7203.5049-0.10385

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: 98.4% (cumulative 98.4%)1PC2: 1.2% (cumulative 99.6%)2PC3: 0.2% (cumulative 99.8%)3PC4: 0.1% (cumulative 99.9%)4PC5: 0.1% (cumulative 100.0%)5PC6: 0.0% (cumulative 100.0%)6PC7: 0.0% (cumulative 100.0%)7PC8: 0.0% (cumulative 100.0%)8PC9: 0.0% (cumulative 100.0%)9PC10: 0.0% (cumulative 100.0%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
View explained variance values
Variance per displayed principal component
ComponentSpectral variance
PC198.36%
PC21.21%
PC30.19%
PC40.13%
PC50.06%
PC60.02%
PC70.01%
PC80.01%
PC90.00%
PC100.00%

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

0 experimental metadata fields (M) · 1 informative targets (Y).

VariableRoleDistinct valuesCompleteRange / balance
groupY6100%IR 1.008

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 1

group

target · categorical

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

group classesRubberRubber: 240240FoamFoam: 240240PCPC: 240240FoilFoil: 2402403D3D: 240240TextileTextile: 238238
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 0
Classes
?Number of distinct recorded category values.
6
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.
Rubber (240)

Metadata 7

file_url

metadata · categorical

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

file_url classeshttps://zenodo.org/api/record…https://zenodo.org/api/records/18471662/files/measurements_125.csv/content: 720720https://zenodo.org/api/record…https://zenodo.org/api/records/18471662/files/measurements_2151.csv/content: 718718
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 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.
https://zenodo.org/api/records/18471662/files/measurements_125.csv/content (720)

axis_min

metadata · numeric

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

axis_min distribution0250500750350 – 373.3: 718373.3 – 396.5: 0396.5 – 419.8: 0419.8 – 443: 0443 – 466.3: 0466.3 – 489.5: 0489.5 – 512.8: 0512.8 – 536: 0536 – 559.3: 0559.3 – 582.5: 0582.5 – 605.8: 0605.8 – 629: 0629 – 652.3: 0652.3 – 675.6: 0675.6 – 698.8: 0698.8 – 722.1: 0722.1 – 745.3: 0745.3 – 768.6: 0768.6 – 791.8: 0791.8 – 815.1: 0815.1 – 838.3: 0838.3 – 861.6: 0861.6 – 884.8: 0884.8 – 908.1: 7201002005001,000
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
629.4 ± 279
Median
?50th percentile: half the non-missing values lie at or below it.
908.1
Range
?Smallest and largest recorded non-missing values.
350 – 908.1
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.443
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.0028 / -2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

axis_max

metadata · numeric

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

axis_max distribution02505007501676 – 1711: 7201711 – 1745: 01745 – 1779: 01779 – 1814: 01814 – 1848: 01848 – 1882: 01882 – 1916: 01916 – 1951: 01951 – 1985: 01985 – 2019: 02019 – 2054: 02054 – 2088: 02088 – 2122: 02122 – 2157: 02157 – 2191: 02191 – 2225: 02225 – 2260: 02260 – 2294: 02294 – 2328: 02328 – 2363: 02363 – 2397: 02397 – 2431: 02431 – 2466: 02466 – 2,500: 7181,0002,0005,00010,000
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
2088 ± 412
Median
?50th percentile: half the non-missing values lie at or below it.
1676
Range
?Smallest and largest recorded non-missing values.
1676 – 2,500
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.197
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.0028 / -2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

n_points_original

metadata · numeric

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

n_points_original distribution0250500750125 – 209.4: 720209.4 – 293.8: 0293.8 – 378.2: 0378.2 – 462.7: 0462.7 – 547.1: 0547.1 – 631.5: 0631.5 – 715.9: 0715.9 – 800.3: 0800.3 – 884.8: 0884.8 – 969.2: 0969.2 – 1054: 01054 – 1,138: 01,138 – 1222: 01222 – 1307: 01307 – 1391: 01391 – 1476: 01476 – 1560: 01560 – 1644: 01644 – 1729: 01729 – 1813: 01813 – 1898: 01898 – 1982: 01982 – 2067: 02067 – 2,151: 71801,0002,0003,000
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1137 ± 1.01e+03
Median
?50th percentile: half the non-missing values lie at or below it.
125
Range
?Smallest and largest recorded non-missing values.
125 – 2,151
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.892
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.0028 / -2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

id

metadata · categorical

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

id classes575575: 66806806: 44808808: 44774774: 44766766: 44859859: 44401401: 44481481: 44902902: 44762762: 44+10 more+10 more: 4040
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 0
Classes
?Number of distinct recorded category values.
363
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.
3
Top class
?Most frequent recorded category and its observation count.
575 (6)

sample

metadata · numeric

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

sample distribution02550750 – 32.38: 5732.38 – 64.75: 6064.75 – 97.12: 6697.12 – 129.5: 63129.5 – 161.9: 62161.9 – 194.2: 66194.2 – 226.6: 62226.6 – 259: 61259 – 291.4: 66291.4 – 323.8: 63323.8 – 356.1: 64356.1 – 388.5: 61388.5 – 420.9: 64420.9 – 453.2: 63453.2 – 485.6: 62485.6 – 518: 63518 – 550.4: 62550.4 – 582.8: 60582.8 – 615.1: 64615.1 – 647.5: 61647.5 – 679.9: 64679.9 – 712.2: 63712.2 – 744.6: 38744.6 – 777: 230200400600800
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
373.1 ± 215
Median
?50th percentile: half the non-missing values lie at or below it.
371.5
Range
?Smallest and largest recorded non-missing values.
0 – 777
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.576
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.024 / -1.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

fold

metadata · numeric

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

fold distribution01002003000 – 0.1667: 2880.1667 – 0.3333: 00.3333 – 0.5: 00.5 – 0.6667: 00.6667 – 0.8333: 00.8333 – 1: 01 – 1.167: 2881.167 – 1.333: 01.333 – 1.5: 01.5 – 1.667: 01.667 – 1.833: 01.833 – 2: 02 – 2.167: 2882.167 – 2.333: 02.333 – 2.5: 02.5 – 2.667: 02.667 – 2.833: 02.833 – 3: 03 – 3.167: 2873.167 – 3.333: 03.333 – 3.5: 03.5 – 3.667: 03.667 – 3.833: 03.833 – 4: 28701234
n / missing
?Recorded observation count and number of missing values for this variable.
1,438 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.998 ± 1.41
Median
?50th percentile: half the non-missing values lie at or below it.
2
Range
?Smallest and largest recorded non-missing values.
0 – 4
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.708
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.0022 / -1.3
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no
Constant metadata 12

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

  • article_urlhttps://www.sciencedirect.com/science/article/pii/S2352340926004713
  • doi_dataset10.5281/zenodo.18471662
  • doi_publication10.1016/j.dib.2026.112920
  • licenseCreative Commons Attribution 4.0 International
  • license_idcc-by-4.0
  • license_urlhttps://creativecommons.org/licenses/by/4.0/
  • rights_statusexplicit_open
  • usage_scopepublic_reuse_possible
  • public_release_allowedTrue
  • spectroscopy_typeNIR
  • axis_unitnm
  • notesRefuse-derived fuel particle spectra with class labels and predefined subset folds.

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
Samples768
Observations (total)1,438
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("zenodo_twinspectra_rdf_nir")            # 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