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OSSL LUCAS Woodwell soil vis-NIR and MIR

ossl · NIR

OSSL LUCAS Woodwell soil vis-NIR and MIR. Origin database composed from 2 standardized v2.0 leaves: 2 spectral source(s), 12 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2ossl
Original source available without a Dataverse token. The catalog uses the private tier for restricted or uncleared redistribution rights. You can obtain original resources from the source; their license still applies. Raw retrieval and automatic assembly are separate; use the loading example below.
589
samples
2,777
wavelengths
2
sources
12
targets
26
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

ContributorOSSL_NIRS
Conversion statuspartial
Origin · url [open]https://storage.googleapis.com/soilspec4gg-public/ossl_soillab_L1_v1.2.csv.gz
Origin · url [open]https://storage.googleapis.com/soilspec4gg-public/ossl_visnir_L0_v1.2.csv.gz
Origin · url [open]https://storage.googleapis.com/soilspec4gg-public/ossl_soilsite_L0_v1.2.csv.gz

Governance & integrity

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

Tierprivate
LicenseLicenseRef-not-cleared
Permitted useResearch and benchmarking; private use only.
Access policyManual download / private-use-only per source.
RedistributionRecovered from local initial-source exports; rights not cleared for redistribution.
Content version1.1.0
Schema / protocol2.0
Content hashda6ec347d3d8b433…
Processing hash0550362e7ed6628a…
Metadata hash6e48b2b2e2ee3b00…

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 score0.62
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.

OSSL LUCAS Woodwell soil vis-NIR and MIR property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureOSSL LUCAS Woodwell soil vis-NIR and MIR — integrity: 0.23OSSL LUCAS Woodwell soil vis-NIR and MIR — noise: 0.00OSSL LUCAS Woodwell soil vis-NIR and MIR — artefacts: 1.00OSSL LUCAS Woodwell soil vis-NIR and MIR — baseline: 0.93OSSL LUCAS Woodwell soil vis-NIR and MIR — PCA outliers: 0.49OSSL LUCAS Woodwell soil vis-NIR and MIR — reference: 0.99OSSL LUCAS Woodwell soil vis-NIR and MIR — structure: 0.72OSSL LUCAS Wood…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.
0.23
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.
0.93
PCA outliers
?Combines relative PCA residual and score-distance tails. Valid rare spectra can produce a high value.
0.49
Distance to average spectrum
?Dispersion around this dataset's mean spectrum, using distance, shape and shift summaries.
0.99
Repeatability
?Dispersion among observations sharing an ID. Interpretation depends on the documented meaning of that ID.
unavailable
Multi-regime structure
?Variation in local density in PCA space. May reflect legitimate batches or subpopulations.
0.72

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: 0.850.85Offset compatible with a different white referenceOffset compatible with a different white reference: 0.730.73Signature compatible with a different backgroundSignature compatible with a different background: 0.670.67Signature compatible with a population shiftSignature compatible with a population shift: 0.500.50Signature compatible with clippingSignature compatible with clipping: 0.430.43High spectral roughness signatureHigh spectral roughness signature: 0.360.36Flat spectrum/weak signalFlat spectrum/weak signal: 0.110.11

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_visnir0.85strong100 %Spike rate 1.00, Jump rate 1.00, RMS/SAM to mean spectrum 1.00Break at detector junctions, local calibration or different probe.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Offset compatible with a different white referenceX_visnir0.73strong100 %Baseline/mean/area 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_visnir0.67medium100 %Baseline/mean/area 1.00, RMS/SAM to mean spectrum 1.00, PCA Q 0.53Systematic 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.
Signature compatible with a population shiftX_visnir0.50medium100 %RMS/SAM to mean spectrum 1.00, PCA structure 0.85, Mahalanobis / T2 0.46Different 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.
Signature compatible with clippingX_visnir0.43medium100 %Baseline/mean/area 1.00, Jump rate 1.00, PCA Q 0.53Detector 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.
High spectral roughness signatureX_visnir0.36weak100 %Spike rate 1.00, RMS/SAM to mean spectrum 1.00, PCA Q 0.53Weak 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.
Flat spectrum/weak signalX_visnir0.11weak100 %PCA Q 0.53Bad 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_mir—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
recovered_spectra589589
recovered_spectra589589

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

recovered_spectra

X_mir · NIR · unknown

Read the signal and variation summaries for this source. Axis unit: none; 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.

recovered_spectra spectra1.01.52.02.53.001,0002,0003,0004,000q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / none600none — median 2.202 (q25–q75 2.055–2.341)624none — median 2.244 (q25–q75 2.116–2.381)648none — median 2.268 (q25–q75 2.125–2.395)674none — median 2.249 (q25–q75 2.107–2.376)698none — median 2.34 (q25–q75 2.241–2.458)722none — median 2.217 (q25–q75 2.075–2.323)746none — median 2.171 (q25–q75 2.058–2.287)772none — median 2.167 (q25–q75 2.047–2.281)796none — median 2.196 (q25–q75 2.065–2.301)820none — median 2.229 (q25–q75 2.142–2.312)844none — median 2.069 (q25–q75 1.973–2.17)870none — median 2.036 (q25–q75 1.926–2.139)894none — median 2.045 (q25–q75 1.918–2.141)918none — median 2.093 (q25–q75 1.965–2.198)942none — median 2.086 (q25–q75 1.964–2.188)966none — median 2.076 (q25–q75 1.942–2.187)992none — median 2.053 (q25–q75 1.918–2.198)1,016none — median 2.016 (q25–q75 1.875–2.179)1,040none — median 1.957 (q25–q75 1.809–2.128)1,064none — median 1.896 (q25–q75 1.702–2.07)1,090none — median 1.841 (q25–q75 1.636–2.054)1,114none — median 1.874 (q25–q75 1.661–2.078)1,138none — median 1.858 (q25–q75 1.657–2.061)1,162none — median 1.929 (q25–q75 1.733–2.114)1,188none — median 1.843 (q25–q75 1.645–2.043)1,212none — median 1.786 (q25–q75 1.609–1.99)1,236none — median 1.831 (q25–q75 1.671–2.028)1,260none — median 1.965 (q25–q75 1.804–2.14)1,284none — median 2.102 (q25–q75 1.96–2.223)1,310none — median 2.186 (q25–q75 2.069–2.285)1,334none — median 2.218 (q25–q75 2.063–2.332)1,358none — median 2.205 (q25–q75 2.056–2.344)1,382none — median 2.199 (q25–q75 2.064–2.335)1,408none — median 2.171 (q25–q75 2.072–2.3)1,432none — median 2.156 (q25–q75 2.057–2.273)1,456none — median 2.115 (q25–q75 2.013–2.23)1,480none — median 2.055 (q25–q75 1.956–2.183)1,506none — median 2.031 (q25–q75 1.931–2.145)1,530none — median 2.018 (q25–q75 1.922–2.144)1,554none — median 1.97 (q25–q75 1.865–2.112)1,578none — median 2.024 (q25–q75 1.923–2.17)1,602none — median 2.127 (q25–q75 2.027–2.262)1,628none — median 2.173 (q25–q75 2.057–2.305)1,652none — median 2.134 (q25–q75 2.024–2.286)1,676none — median 2.072 (q25–q75 1.968–2.206)1,700none — median 1.943 (q25–q75 1.843–2.071)1,726none — median 1.82 (q25–q75 1.726–1.932)1,750none — median 1.737 (q25–q75 1.654–1.838)1,774none — median 1.718 (q25–q75 1.655–1.825)1,798none — median 1.739 (q25–q75 1.658–1.83)1,824none — median 1.623 (q25–q75 1.562–1.7)1,848none — median 1.621 (q25–q75 1.555–1.692)1,872none — median 1.674 (q25–q75 1.591–1.774)1,896none — median 1.626 (q25–q75 1.549–1.717)1,920none — median 1.531 (q25–q75 1.474–1.606)1,946none — median 1.521 (q25–q75 1.46–1.593)1,970none — median 1.523 (q25–q75 1.458–1.602)1,994none — median 1.521 (q25–q75 1.451–1.601)2,018none — median 1.472 (q25–q75 1.409–1.545)2,044none — median 1.404 (q25–q75 1.336–1.486)2,068none — median 1.358 (q25–q75 1.288–1.456)2,092none — median 1.345 (q25–q75 1.274–1.444)2,116none — median 1.335 (q25–q75 1.264–1.435)2,142none — median 1.337 (q25–q75 1.267–1.433)2,166none — median 1.317 (q25–q75 1.246–1.42)2,190none — median 1.306 (q25–q75 1.236–1.412)2,214none — median 1.309 (q25–q75 1.24–1.411)2,238none — median 1.313 (q25–q75 1.247–1.411)2,264none — median 1.301 (q25–q75 1.231–1.402)2,288none — median 1.284 (q25–q75 1.216–1.395)2,312none — median 1.28 (q25–q75 1.208–1.392)2,336none — median 1.282 (q25–q75 1.211–1.392)2,362none — median 1.277 (q25–q75 1.205–1.39)2,386none — median 1.274 (q25–q75 1.202–1.385)2,410none — median 1.274 (q25–q75 1.2–1.384)2,434none — median 1.272 (q25–q75 1.2–1.382)2,458none — median 1.277 (q25–q75 1.203–1.388)2,484none — median 1.304 (q25–q75 1.227–1.408)2,508none — median 1.338 (q25–q75 1.245–1.456)2,532none — median 1.332 (q25–q75 1.242–1.446)2,556none — median 1.319 (q25–q75 1.237–1.428)2,582none — median 1.322 (q25–q75 1.242–1.43)2,606none — median 1.322 (q25–q75 1.247–1.425)2,630none — median 1.314 (q25–q75 1.238–1.427)2,654none — median 1.315 (q25–q75 1.241–1.431)2,680none — median 1.324 (q25–q75 1.247–1.444)2,704none — median 1.336 (q25–q75 1.255–1.454)2,728none — median 1.347 (q25–q75 1.267–1.465)2,752none — median 1.36 (q25–q75 1.279–1.479)2,776none — median 1.375 (q25–q75 1.295–1.497)2,802none — median 1.399 (q25–q75 1.314–1.518)2,826none — median 1.426 (q25–q75 1.34–1.543)2,850none — median 1.487 (q25–q75 1.398–1.602)2,874none — median 1.503 (q25–q75 1.416–1.62)2,900none — median 1.514 (q25–q75 1.428–1.639)2,924none — median 1.552 (q25–q75 1.466–1.687)2,948none — median 1.552 (q25–q75 1.465–1.685)2,972none — median 1.56 (q25–q75 1.467–1.686)2,998none — median 1.556 (q25–q75 1.461–1.684)3,022none — median 1.569 (q25–q75 1.471–1.7)3,046none — median 1.594 (q25–q75 1.489–1.72)3,070none — median 1.615 (q25–q75 1.51–1.748)3,094none — median 1.634 (q25–q75 1.533–1.774)3,120none — median 1.66 (q25–q75 1.551–1.804)3,144none — median 1.686 (q25–q75 1.573–1.83)3,168none — median 1.711 (q25–q75 1.597–1.862)3,192none — median 1.738 (q25–q75 1.615–1.883)3,218none — median 1.763 (q25–q75 1.64–1.91)3,242none — median 1.782 (q25–q75 1.653–1.931)3,266none — median 1.796 (q25–q75 1.665–1.946)3,290none — median 1.809 (q25–q75 1.674–1.957)3,316none — median 1.819 (q25–q75 1.686–1.971)3,340none — median 1.832 (q25–q75 1.697–1.986)3,364none — median 1.846 (q25–q75 1.704–1.996)3,388none — median 1.853 (q25–q75 1.71–2.004)3,412none — median 1.853 (q25–q75 1.708–2.003)3,438none — median 1.85 (q25–q75 1.705–2.003)3,462none — median 1.84 (q25–q75 1.696–1.995)3,486none — median 1.829 (q25–q75 1.686–1.983)3,510none — median 1.818 (q25–q75 1.677–1.972)3,536none — median 1.819 (q25–q75 1.681–1.972)3,560none — median 1.824 (q25–q75 1.687–1.979)3,584none — median 1.837 (q25–q75 1.692–1.989)3,608none — median 1.879 (q25–q75 1.714–2.023)3,634none — median 1.889 (q25–q75 1.708–2.041)3,658none — median 1.784 (q25–q75 1.598–1.946)3,682none — median 1.596 (q25–q75 1.446–1.767)3,706none — median 1.482 (q25–q75 1.339–1.682)3,730none — median 1.265 (q25–q75 1.181–1.351)3,756none — median 1.197 (q25–q75 1.133–1.277)3,780none — median 1.175 (q25–q75 1.115–1.245)3,804none — median 1.163 (q25–q75 1.105–1.24)3,828none — median 1.156 (q25–q75 1.098–1.234)3,854none — median 1.15 (q25–q75 1.093–1.23)3,878none — median 1.147 (q25–q75 1.094–1.225)3,902none — median 1.146 (q25–q75 1.093–1.223)3,926none — median 1.145 (q25–q75 1.093–1.221)3,952none — median 1.144 (q25–q75 1.091–1.219)3,976none — median 1.142 (q25–q75 1.089–1.219)4,000none — median 1.14 (q25–q75 1.086–1.218)

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.
1,701
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
600–4,000 none
Mean spacing
?Average difference between adjacent spectral-axis coordinates; compare only within the same unit.
2 none
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.
589

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.
0.892 – 3.48
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
1.16 – 2.35
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
1.704
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
5792
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
1.188
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
0.00021192
Roughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR.
8e+03
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.
1.19
Smoothness
?Mean per-spectrum RMS of second differences, in signal units. Smaller values indicate smoother spectra under this protocol.
0.007521
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.
282

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.
54,080
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
5.40%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
28,163
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
2.81%
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.
-0.73146
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.0061241
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.0089085
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
0.14622
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
0.33927
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.062539
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.11101
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
0.37946
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
0.22554
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
0.20094
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.
3.5
Hotelling T2 p95/median
?Hotelling T² measures distance within the retained PCA subspace, scaled by component variance. Ratio of the 95th percentile to the median.
3
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.
1.7
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.
3.9
PCs → 95% var
?Number of principal components needed to explain 95% of spectral variance, when reached by the computed projection.
6
PCs → 99% var
?Number of principal components needed to explain 99% of spectral variance, when reached by the computed projection.
14
Top-10 cum. var
?Fraction of spectral variance explained by up to the first ten computed principal components, displayed as a percentage.
98.3%
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		1.70360.86strongAtypical value: Too light / background visible or Too darkBackground, geometrymean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Overall amplitudeArea under curve
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit. Scoring: alert reuses baseline/shape drift because area scale depends on axis and units. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.area_under_curve		5792.20.86strongAtypical value: Illumination difference or NormalProbe distancetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Overall amplitudePeak-to-peak (PTP)
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum. Scoring: alert increases when dynamic range is abnormally flat. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.peak_to_peak		1.18790.00weakStrong 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		0.145120.00weakNormal 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		0.000211920.00weakStableLamp, 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		8038.90.00weakGood 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		68.230.00weakReliable 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		54,0801.00strongArtifactsCosmic 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		5.4%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		28,1631.00strongDetector 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		2.81%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		0.0002%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		-0.731460.86strongDriftIlluminationlinear 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		0.00612410.36weakSmoothBackground, 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		0.00890850.10weakFlatBiology or artifactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Multivariate outliersPCA Q (SPE)
?Q (squared prediction error) is variation left outside the retained PCA subspace. The displayed ratio compares its 95th percentile with its median. Scoring: alert = min(1, pca_q_ratio / 8). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.pca_q_ratio		3.49530.44mediumAtypical 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		3.04120.38weakCentralNatural 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		1.74390.44mediumGlobal 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		0.339270.80strongDifferent 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		0.111010.32weakSimilarBackground, 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		0.428590.58mediumSubpopulationsDifferent 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		1.75150.38weakNormal 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 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		0.531860.58mediumAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source recovered_spectra: 589 of 589 source observations are plotted. PC1 captures 61.4% and PC2 16.7% of the reported spectral variance: 78.2% together; 21.8% 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.

recovered_spectra PCA score plot-20-1001020-1001020PC1 -1.834 · PC2 -1.763PC1 -2.621 · PC2 0.7936PC1 -1.074 · PC2 0.9302PC1 -3.498 · PC2 0.3643PC1 12.98 · PC2 1.378PC1 7.371 · PC2 0.09939PC1 8.846 · PC2 0.8271PC1 -0.1193 · PC2 -0.5367PC1 10.68 · PC2 1.424PC1 17.46 · PC2 3.46PC1 5.332 · PC2 -0.3475PC1 -6.005 · PC2 -2.714PC1 0.8062 · PC2 -1.276PC1 -2.232 · PC2 -0.5873PC1 0.2644 · PC2 3.529PC1 1.12 · PC2 11.48PC1 -2.223 · PC2 -2.866PC1 3.778 · PC2 4.422PC1 3.599 · PC2 9.524PC1 -9.012 · PC2 1.555PC1 -4.394 · PC2 0.7254PC1 3.652 · PC2 15.09PC1 3.902 · PC2 7.243PC1 -7.588 · PC2 -0.3741PC1 -4.821 · PC2 -0.4583PC1 3.812 · PC2 0.4344PC1 -5.17 · PC2 0.4012PC1 2.147 · PC2 0.8247PC1 1.69 · PC2 -0.8037PC1 -7.96 · PC2 1.416PC1 13.85 · PC2 2.195PC1 -7.557 · PC2 0.4994PC1 -6.15 · PC2 0.1007PC1 -9.967 · PC2 -3.792PC1 3.065 · PC2 -0.1734PC1 2.717 · PC2 -0.05024PC1 -5.32 · PC2 -2.035PC1 9.179 · PC2 -3.677PC1 -1.034 · PC2 1.361PC1 -4.165 · PC2 -1.923PC1 4.805 · PC2 13.72PC1 -1.902 · PC2 -1.036PC1 -1.478 · PC2 -1.402PC1 14.5 · PC2 0.7757PC1 3.387 · PC2 0.1187PC1 0.3478 · PC2 -1.137PC1 7.629 · PC2 2.513PC1 -9.015 · PC2 -1.836PC1 -5.725 · PC2 -2.103PC1 0.2261 · PC2 11.18PC1 1.721 · PC2 0.8848PC1 0.4613 · PC2 -0.05352PC1 -3.339 · PC2 1.641PC1 3.346 · PC2 4.499PC1 11.92 · PC2 -0.5725PC1 -4.602 · PC2 0.2788PC1 0.6589 · PC2 1.053PC1 5.193 · PC2 5.829PC1 -2.014 · PC2 0.5523PC1 -5.701 · PC2 1.919PC1 -3.521 · PC2 -0.9196PC1 -8.485 · PC2 -1.383PC1 5.282 · PC2 -1.818PC1 0.6625 · PC2 1.967PC1 4.113 · PC2 2.308PC1 3.756 · PC2 11.5PC1 3.028 · PC2 10.25PC1 -4.086 · PC2 -0.481PC1 0.5283 · PC2 3.752PC1 -3.683 · PC2 2.704PC1 -7.264 · PC2 -0.2305PC1 -3.157 · PC2 2.89PC1 -4.011 · PC2 -0.1119PC1 -2.595 · PC2 0.2217PC1 3.935 · PC2 7.457PC1 0.1092 · PC2 1.845PC1 -2.646 · PC2 -0.2335PC1 -6.531 · PC2 -2.075PC1 1.014 · PC2 -0.4078PC1 -13.96 · PC2 -1.415PC1 -6.487 · PC2 -2.479PC1 1.289 · PC2 2.787PC1 3.775 · PC2 2.314PC1 -1.238 · PC2 -1.818PC1 0.8892 · PC2 -1.874PC1 6.251 · PC2 -0.1756PC1 2.555 · PC2 0.8736PC1 2.781 · PC2 9.984PC1 -4.273 · PC2 2.832PC1 -4.876 · PC2 -0.6589PC1 1.512 · PC2 10.43PC1 -7.595 · PC2 -1.576PC1 9.384 · PC2 11.16PC1 6.016 · PC2 12.62PC1 -9.103 · PC2 3.996PC1 4.474 · PC2 8.745PC1 2.151 · PC2 -1.346PC1 4.509 · PC2 -0.989PC1 3.969 · PC2 2.469PC1 -7.606 · PC2 -0.6049PC1 1.56 · PC2 -1.463PC1 1.679 · PC2 -0.3821PC1 3.188 · PC2 5.539PC1 -8.963 · PC2 -3.084PC1 -2.758 · PC2 -0.9802PC1 4.907 · PC2 1.448PC1 -2.391 · PC2 -0.5905PC1 -0.4144 · PC2 -0.6072PC1 -3.853 · PC2 -0.6387PC1 -1.048 · PC2 -0.5794PC1 -4.281 · PC2 1.707PC1 -6.306 · PC2 1.522PC1 3.192 · PC2 0.5342PC1 -0.2199 · PC2 14.02PC1 2.492 · PC2 0.5192PC1 3.721 · PC2 -0.09397PC1 -3.349 · PC2 1.099PC1 -3.13 · PC2 5.416PC1 3.501 · PC2 4.918PC1 -4.205 · PC2 -3.832PC1 -3.579 · PC2 -3.178PC1 -4.938 · PC2 -2.662PC1 -3.946 · PC2 -5.641PC1 5.812 · PC2 -6.803PC1 -0.6156 · PC2 1.443PC1 3.145 · PC2 -4.553PC1 1.519 · PC2 2.896PC1 -1.062 · PC2 -1.547PC1 2.002 · PC2 1.04PC1 5.816 · PC2 3.011PC1 3.689 · PC2 -1.481PC1 -2.714 · PC2 -4.197PC1 -2.21 · PC2 -4.254PC1 1.714 · PC2 2.822PC1 2.377 · PC2 -2.225PC1 9.944 · PC2 -0.5035PC1 -2.469 · PC2 -2.837PC1 3.753 · PC2 0.2696PC1 4.837 · PC2 -0.1156PC1 -4.609 · PC2 3.026PC1 2.421 · PC2 -2.352PC1 2.676 · PC2 -3.334PC1 -0.8729 · PC2 -2.682PC1 -1.485 · PC2 -1.137PC1 7.49 · PC2 -0.2349PC1 4.788 · PC2 3.766PC1 -4.275 · PC2 3.298PC1 9.908 · PC2 -1.197PC1 0.05272 · PC2 -1.929PC1 3.799 · PC2 -4.999PC1 2.27 · PC2 0.2015PC1 -6.602 · PC2 5.427PC1 -4.522 · PC2 -0.959PC1 1.822 · PC2 -3.442PC1 8.479 · PC2 -2.984PC1 -2.932 · PC2 -2.364PC1 12.84 · PC2 -3.897PC1 3.762 · PC2 -2.777PC1 2.855 · PC2 -2.745PC1 -3.255 · PC2 0.6818PC1 12.72 · PC2 -1.028PC1 1.205 · PC2 -3.159PC1 -2.675 · PC2 0.2039PC1 0.09857 · PC2 -1.402PC1 -3.22 · PC2 -0.6734PC1 -9.034 · PC2 2.408PC1 -5.406 · PC2 -0.8908PC1 -2.643 · PC2 -0.08517PC1 -6.623 · PC2 3.673PC1 -11.37 · PC2 0.1961PC1 5.35 · PC2 1.931PC1 -1.225 · PC2 -2.819PC1 -2.86 · PC2 -1.641PC1 -1.876 · PC2 -2.561PC1 6.097 · PC2 -1.925PC1 1.642 · PC2 -2.595PC1 9.246 · PC2 1.229PC1 -0.4123 · PC2 1.462PC1 -3.089 · PC2 -4.699PC1 -6.589 · PC2 -0.4983PC1 -10.1 · PC2 -0.3545PC1 -2.022 · PC2 -3.477PC1 -10.16 · PC2 2.272PC1 8.459 · PC2 -5.618PC1 -3.038 · PC2 -2.1PC1 1.515 · PC2 -2.829PC1 -0.7658 · PC2 -3.314PC1 -7.465 · PC2 3.187PC1 2.74 · PC2 -4.609PC1 9.137 · PC2 -5.36PC1 10.69 · PC2 0.6917PC1 -5.469 · PC2 -3.231PC1 -4.343 · PC2 -3.115PC1 0.3248 · PC2 2.199PC1 -1.349 · PC2 -2.173PC1 1.03 · PC2 -0.1879PC1 -3.224 · PC2 -0.7817PC1 16.87 · PC2 2.487PC1 -2.577 · PC2 -1.444PC1 -4.232 · PC2 -2.798PC1 1.323 · PC2 3.909PC1 -4.723 · PC2 -2.406PC1 3.119 · PC2 -2.288PC1 3.527 · PC2 -2.77PC1 -2.513 · PC2 2.962PC1 4.387 · PC2 -0.6168PC1 0.3711 · PC2 2.651PC1 0.8073 · PC2 -2.894PC1 -1.476 · PC2 0.03862PC1 -7.136 · PC2 4.305PC1 -3.057 · PC2 4.29PC1 -1.328 · PC2 -1.141PC1 0.08337 · PC2 3.332PC1 -6.702 · PC2 3.963PC1 10.22 · PC2 1.988PC1 12.26 · PC2 0.5364PC1 14.21 · PC2 -0.6316PC1 2.301 · PC2 -1.291PC1 -4.733 · PC2 5.371PC1 0.4816 · PC2 9.879PC1 1.629 · PC2 -2.154PC1 14.05 · PC2 3.451PC1 -1.785 · PC2 -3.465PC1 -0.3247 · PC2 -3.074PC1 5.689 · PC2 -2.16PC1 -0.01867 · PC2 -2.945PC1 1.828 · PC2 -3.413PC1 5.327 · PC2 -1.101PC1 0.3649 · PC2 3.108PC1 -1.36 · PC2 -1.917PC1 -4.987 · PC2 0.1032PC1 7.956 · PC2 -2.297PC1 0.2207 · PC2 -5.664PC1 -6.946 · PC2 0.409PC1 -3.601 · PC2 -3.37PC1 3.327 · PC2 -0.2675PC1 -9.121 · PC2 1.06PC1 -3.036 · PC2 -1.179PC1 -2 · PC2 -4.195PC1 2.697 · PC2 0.008589PC1 0.5826 · PC2 -2.712PC1 -4.234 · PC2 -3.705PC1 -4.569 · PC2 -3.213PC1 -2.944 · PC2 -1.302PC1 -8.508 · PC2 0.4229PC1 15.21 · PC2 2.433PC1 1.521 · PC2 -1.276PC1 -5.289 · PC2 2.636PC1 -11.18 · PC2 -3.363PC1 -3.505 · PC2 1.21PC1 -6.379 · PC2 -2.52PC1 2.428 · PC2 -5.718PC1 -0.2157 · PC2 -0.9267PC1 -1.4 · PC2 0.3275PC1 3.245 · PC2 -8.021PC1 1.281 · PC2 -4.941PC1 2.998 · PC2 -2.188PC1 -3.866 · PC2 2.187PC1 -4.836 · PC2 -2.129PC1 -0.4157 · PC2 -1.891PC1 -3.985 · PC2 -0.7179PC1 -3.668 · PC2 -1.224PC1 -8.428 · PC2 4.033PC1 -6.742 · PC2 3.878PC1 3.598 · PC2 -2.107PC1 -0.3259 · PC2 -0.3888PC1 13.42 · PC2 -0.5685PC1 13.3 · PC2 -4.67PC1 -1.364 · PC2 -1.393PC1 -2.915 · PC2 -4.64PC1 -10.56 · PC2 -1.559PC1 -1.413 · PC2 -3.036PC1 -2.854 · PC2 -3.452PC1 -3.158 · PC2 -0.9426PC1 -1.292 · PC2 -3.922PC1 -0.441 · PC2 -0.5585PC1 9.314 · PC2 0.5003PC1 1.187 · PC2 4.793PC1 -1.968 · PC2 -3.085PC1 0.1798 · PC2 1.85PC1 -5.866 · PC2 2.268PC1 7.121 · PC2 -1.265PC1 0.4794 · PC2 -4.342PC1 2.303 · PC2 -0.935PC1 14.4 · PC2 0.6032PC1 -6.452 · PC2 2.235PC1 -5.643 · PC2 -2.29PC1 -5.407 · PC2 -0.3929PC1 -2.058 · PC2 -3.777PC1 3.463 · PC2 3.25PC1 -5.089 · PC2 4.282PC1 -0.8548 · PC2 -3.029PC1 1.772 · PC2 0.2561PC1 1.314 · PC2 -5.269PC1 -3.566 · PC2 -2.623PC1 0.8528 · PC2 -1.491PC1 -0.3839 · PC2 -1.293PC1 -3.305 · PC2 -3.064PC1 -5.448 · PC2 -1.214PC1 10.5 · PC2 2.01PC1 12.77 · PC2 1.655PC1 7.789 · PC2 -2.355PC1 -2.068 · PC2 -4.003PC1 2.369 · PC2 -1.938PC1 -6.894 · PC2 1.344PC1 -10.25 · PC2 0.874PC1 9.163 · PC2 2.815PC1 -3.818 · PC2 -1.483PC1 0.0072 · PC2 -4.351PC1 3.05 · PC2 -1.425PC1 3.78 · PC2 -1.655PC1 -0.344 · PC2 0.9112PC1 4.182 · PC2 -0.7187PC1 2.346 · PC2 2.161PC1 1.646 · PC2 -3.282PC1 -3.914 · PC2 -3.774PC1 -0.2523 · PC2 -5.613PC1 -3.649 · PC2 -2.957PC1 -6.55 · PC2 0.4219PC1 -3.488 · PC2 1.911PC1 0.3076 · PC2 -1.677PC1 4.144 · PC2 3.449PC1 -0.137 · PC2 -2.055PC1 -0.8861 · PC2 -1.298PC1 -2.371 · PC2 -0.8699PC1 13.55 · PC2 0.4799PC1 3.603 · PC2 0.319PC1 -8.903 · PC2 -1.637PC1 -5.742 · PC2 4.727PC1 -2.965 · PC2 -3.702PC1 19.52 · PC2 2.624PC1 -5.53 · PC2 1.307PC1 -6.319 · PC2 2.87PC1 -0.0963 · PC2 -0.4385PC1 -3.034 · PC2 3.201PC1 7.742 · PC2 -3.369PC1 12.88 · PC2 2.182PC1 7.807 · PC2 -2.002PC1 7.125 · PC2 -1.384PC1 2.146 · PC2 -2.936PC1 -3.158 · PC2 -3.308PC1 12.86 · PC2 0.5264PC1 -4.461 · PC2 0.415PC1 -3.871 · PC2 -6.79PC1 3.267 · PC2 2.459PC1 6.286 · PC2 -0.9265PC1 -1.347 · PC2 -3.748PC1 2.925 · PC2 -1.936PC1 -3.393 · PC2 -1.545PC1 -4.511 · PC2 -3.302PC1 -5.236 · PC2 -1.718PC1 9.669 · PC2 -1.544PC1 0.3279 · PC2 -2.61PC1 -9.349 · PC2 -2.613PC1 -5.048 · PC2 2.106PC1 -1.033 · PC2 2.344PC1 15.83 · PC2 1.827PC1 -5.317 · PC2 0.1521PC1 -7.088 · PC2 0.295PC1 -10.23 · PC2 1.531PC1 -0.2311 · PC2 -0.9512PC1 8.432 · PC2 1.029PC1 -12.67 · PC2 -1.126PC1 -3.196 · PC2 -0.3454PC1 -10.05 · PC2 2.953PC1 -3.078 · PC2 0.04476PC1 3.399 · PC2 5.092PC1 -10.35 · PC2 5.443PC1 -4.095 · PC2 3.243PC1 -3.601 · PC2 -2.262PC1 -2.79 · PC2 -1.618PC1 8.44 · PC2 -2.519PC1 5.978 · PC2 -2.011PC1 -3.208 · PC2 0.9006PC1 -10.18 · PC2 2.081PC1 -1.265 · PC2 -4.471PC1 10.85 · PC2 0.3987PC1 -1.726 · PC2 -1.655PC1 1.172 · PC2 4.399PC1 -0.7812 · PC2 0.4317PC1 8.233 · PC2 -1.351PC1 4.264 · PC2 0.5416PC1 -6.621 · PC2 -1.276PC1 0.4419 · PC2 -0.1043PC1 3.57 · PC2 -3.4PC1 -2.891 · PC2 -3.618PC1 0.3894 · PC2 -1.464PC1 -1.833 · PC2 4.007PC1 1.507 · PC2 -3.024PC1 -9.819 · PC2 -0.04612PC1 5.423 · PC2 -2.863PC1 2.427 · PC2 -2.195PC1 -4.752 · PC2 -2.889PC1 6.357 · PC2 -1.432PC1 2.015 · PC2 -1.462PC1 -2.531 · PC2 0.7502PC1 1.471 · PC2 -3.684PC1 4.845 · PC2 -0.2952PC1 6.209 · PC2 -1.11PC1 2.694 · PC2 -1.591PC1 12.27 · PC2 1.703PC1 -7.714 · PC2 4.069PC1 -5.29 · PC2 -0.9349PC1 -4.167 · PC2 2.213PC1 2.291 · PC2 -3.609PC1 -9.219 · PC2 1.272PC1 -1.888 · PC2 -4.227PC1 3.481 · PC2 -2.401PC1 -15.97 · PC2 1.435PC1 -7.639 · PC2 3.873PC1 -0.4199 · PC2 -2.748PC1 15.24 · PC2 3.372PC1 1.228 · PC2 -3.314PC1 -0.02531 · PC2 -0.3058PC1 1.457 · PC2 -3.4PC1 3.921 · PC2 -5.013PC1 -0.4434 · PC2 0.348PC1 -10.31 · PC2 5.678PC1 -4.692 · PC2 -0.7201PC1 -9.762 · PC2 -2.491PC1 -6.48 · PC2 5.35PC1 0.6909 · PC2 -0.5686PC1 -11.94 · PC2 5.023PC1 -5.643 · PC2 2.95PC1 -7.86 · PC2 2.683PC1 -5.426 · PC2 4.764PC1 6.814 · PC2 -0.9146PC1 1.867 · PC2 0.5393PC1 -5.669 · PC2 3.855PC1 -3.684 · PC2 -0.7241PC1 12.82 · PC2 1.865PC1 -7.918 · PC2 2.858PC1 13.37 · PC2 1.379PC1 6.769 · PC2 0.1948PC1 8.762 · PC2 1.41PC1 -4.249 · PC2 3.024PC1 -0.2674 · PC2 0.0756PC1 -1.106 · PC2 -1.957PC1 16.82 · PC2 2.377PC1 -10.3 · PC2 1.998PC1 -1.61 · PC2 -2.32PC1 -0.1727 · PC2 0.6016PC1 -1.444 · PC2 -0.6078PC1 11.18 · PC2 1.315PC1 -4.418 · PC2 0.1223PC1 -4.482 · PC2 2.675PC1 9.072 · PC2 3.029PC1 -3.806 · PC2 -0.9624PC1 -11.52 · PC2 -1.72PC1 0.7677 · PC2 1.823PC1 -0.1876 · PC2 -1.333PC1 -0.6205 · PC2 -4.506PC1 -8.107 · PC2 6.522PC1 -4.507 · PC2 -1.32PC1 10.24 · PC2 -2.205PC1 -5.553 · PC2 0.000219PC1 3.824 · PC2 -2.265PC1 10.55 · PC2 1.321PC1 4.289 · PC2 0.3631PC1 -0.8772 · PC2 0.1443PC1 8.345 · PC2 -5.889PC1 1.907 · PC2 0.6349PC1 -7.036 · PC2 2.51PC1 -2.894 · PC2 0.8411PC1 -2.582 · PC2 1.85PC1 -4.748 · PC2 6.143PC1 10.33 · PC2 4.021PC1 -3.5 · PC2 3.328PC1 -4.74 · PC2 2.218PC1 -6.799 · PC2 -0.1011PC1 -5.781 · PC2 -3.701PC1 -0.6033 · PC2 -1.242PC1 12.3 · PC2 1.37PC1 -15.07 · PC2 3.353PC1 2.68 · PC2 2.134PC1 6.294 · PC2 -0.2057PC1 5.228 · PC2 1.055PC1 -7.164 · PC2 4.381PC1 -12.37 · PC2 3.998PC1 9.909 · PC2 1.006PC1 -6.377 · PC2 5.315PC1 -4.857 · PC2 4.451PC1 3.722 · PC2 3.104PC1 -0.6024 · PC2 -0.8135PC1 16.07 · PC2 2.495PC1 -4.058 · PC2 3.758PC1 4.622 · PC2 -2.575PC1 -3.029 · PC2 -1.061PC1 -3.037 · PC2 0.5929PC1 -1.849 · PC2 2.144PC1 -1.961 · PC2 -0.4637PC1 9.662 · PC2 -2.848PC1 5.687 · PC2 -1.132PC1 0.4186 · PC2 -1.747PC1 0.5215 · PC2 -0.9308PC1 3.421 · PC2 -3.07PC1 4.33 · PC2 -1.745PC1 -3.228 · PC2 -1.28PC1 -4.395 · PC2 3.455PC1 11.92 · PC2 3.483PC1 1.305 · PC2 -0.9727PC1 -2.294 · PC2 1.483PC1 2.924 · PC2 -0.1197PC1 4.395 · PC2 -2.869PC1 3.351 · PC2 -2.893PC1 0.1376 · PC2 -2.3PC1 1.558 · PC2 2.315PC1 0.4439 · PC2 -3.657PC1 1.693 · PC2 -3.479PC1 -9.344 · PC2 0.7527PC1 1.673 · PC2 -0.6687PC1 4.039 · PC2 -1.397PC1 -2.787 · PC2 -2.691PC1 -7.868 · PC2 3.326PC1 -10.09 · PC2 4.651PC1 10.15 · PC2 3.436PC1 13.2 · PC2 1.593PC1 -11.23 · PC2 4.162PC1 7.133 · PC2 -0.2066PC1 -3.852 · PC2 -0.6065PC1 2.674 · PC2 -1.303PC1 -7.784 · PC2 0.2852PC1 1.225 · PC2 -2.147PC1 -7.599 · PC2 -2.147PC1 0.2398 · PC2 -2.686PC1 5.742 · PC2 -3.207PC1 -3.349 · PC2 -1.517PC1 -0.03299 · PC2 -5.105PC1 3.882 · PC2 4.276PC1 -1.516 · PC2 -3.013PC1 -1.387 · PC2 -1.842PC1 -2.727 · PC2 0.3542PC1 -0.059 · PC2 -2.415PC1 -4.741 · PC2 -2.532PC1 11.58 · PC2 -0.2531PC1 1.077 · PC2 -6.629PC1 8.091 · PC2 0.7901PC1 -2.616 · PC2 -0.7119PC1 -4.477 · PC2 -2.29PC1 -5.6 · PC2 -2.061PC1 -2.065 · PC2 -4.31PC1 -3.076 · PC2 -3.434PC1 -8.355 · PC2 -1.813PC1 -8.943 · PC2 3.553PC1 5.273 · PC2 -0.8938PC1 -8.783 · PC2 -3.554PC1 3.088 · PC2 -4.404PC1 -2.645 · PC2 1.602PC1 10.12 · PC2 0.7033PC1 4.865 · PC2 -3.149PC1 1.511 · PC2 0.6948PC1 -4.495 · PC2 -1.725PC1 -2.915 · PC2 0.2068PC1 -1.74 · PC2 3.3PC1 -4.941 · PC2 4.597PC1 -3.344 · PC2 -3.514PC1 -0.2739 · PC2 -2.516PC1 14.37 · PC2 1.346PC1 -6.249 · PC2 -0.4062PC1 -4.663 · PC2 -1.132PC1 -0.6208 · PC2 4.363PC1 9.486 · PC2 1.423PC1 13.7 · PC2 1.81PC1 -7.808 · PC2 4.965PC1 -0.2528 · PC2 0.8526PC1 -0.9984 · PC2 3.05PC1 6.86 · PC2 -1.715PC1 -0.7971 · PC2 -2.828PC1 1.75 · PC2 -3.011PC1 -8.395 · PC2 2.948PC1 -1.488 · PC2 1.368PC1 6.57 · PC2 -1.776PC1 2.445 · PC2 -1.853PC1 -0.7709 · PC2 -2.132PC1 -5.615 · PC2 4.359PC1 3.774 · PC2 -4.65PC1 -1.16 · PC2 -3.299PC1 -0.9198 · PC2 -0.2177PC1 9.547 · PC2 -1.203PC1 4.908 · PC2 -2.81PC1 -4.911 · PC2 0.579PC1 6.095 · PC2 -4.151PC1 -6.935 · PC2 3.533PC1 -6.705 · PC2 -0.3621PC1 -2.073 · PC2 1.597PC1 -13.68 · PC2 -3.099PC1 6.01 · PC2 -1.716PC1 1.109 · PC2 0.1394PC1 -6.726 · PC2 -0.08113PC1 (61.4%)PC2 (16.7%)589 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
1-1.8336-1.7631
2-2.62060.79363
3-1.07420.93022
4-3.49750.36431
512.9811.3775
67.37150.099392
78.84580.82708
8-0.11934-0.53669
910.6821.4242
1017.4613.4601
115.3318-0.34747
12-6.0052-2.7143
130.8062-1.2757
14-2.2324-0.58731
150.264393.5294
161.120511.477
17-2.2233-2.8663
183.77824.4217
193.59889.5242
20-9.01241.5546
21-4.39420.72541
223.651815.087
233.90217.243
24-7.5882-0.37407
25-4.8214-0.4583
263.81230.43444
27-5.16950.40124
282.14690.82468
291.6896-0.80374
30-7.95961.416
3113.8452.1952
32-7.55710.49942
33-6.14990.10074
34-9.9674-3.792
353.065-0.17339
362.7172-0.050238
37-5.3203-2.0347
389.1792-3.6766
39-1.03441.3615
40-4.1648-1.9227
414.80513.719
42-1.9024-1.0363
43-1.4779-1.4016
4414.5030.77572
453.38660.11866
460.34777-1.1368
477.62942.5128
48-9.0148-1.8359
49-5.7252-2.1035
500.2260511.176
511.72050.88481
520.46134-0.053521
53-3.3391.6405
543.34654.4992
5511.915-0.57253
56-4.6020.27881
570.658931.0528
585.19335.8295
59-2.01390.55231
60-5.7011.9195
61-3.5206-0.91964
62-8.4849-1.3835
635.2816-1.8185
640.662541.9665
654.1132.3084
663.755611.5
673.027910.254
68-4.0858-0.48098
690.528293.7515
70-3.68342.7036
71-7.2644-0.23055
72-3.15752.8896
73-4.0109-0.11185
74-2.59540.2217
753.9357.4568
760.109241.8453
77-2.6461-0.2335
78-6.531-2.0748
791.0136-0.40782
80-13.962-1.4146
81-6.4866-2.4788
821.28892.7866
833.77512.3142
84-1.2377-1.8175
850.88917-1.8742
866.2514-0.17555
872.55490.87363
882.78139.9844
89-4.2732.8315
90-4.8762-0.65886
911.512310.428
92-7.595-1.5757
939.383711.164
946.016112.62
95-9.10253.9961
964.47418.7451
972.1515-1.346
984.5086-0.989
993.96852.4691
100-7.6058-0.60492
1011.5597-1.4632
1021.6789-0.38212
1033.18775.5394
104-8.9627-3.0839
105-2.7582-0.98023
1064.90731.4484
107-2.3912-0.59052
108-0.41443-0.6072
109-3.8529-0.63873
110-1.0479-0.57937
111-4.28071.7072
112-6.30641.5218
1133.19190.53421
114-0.2198914.019
1152.49220.51919
1163.7206-0.093972
117-3.34881.099
118-3.12955.4159
1193.50054.9181
120-4.2054-3.8323
121-3.5786-3.1775
122-4.9379-2.6619
123-3.9461-5.6411
1245.8119-6.8029
125-0.615591.4434
1263.1454-4.5532
1271.51932.8961
128-1.0618-1.5472
1292.00181.0399
1305.81623.0114
1313.689-1.4812
132-2.7135-4.1965
133-2.2103-4.2545
1341.71392.8222
1352.3773-2.2251
1369.9442-0.50353
137-2.4689-2.8373
1383.75260.26964
1394.8373-0.11555
140-4.60923.0262
1412.4212-2.3523
1422.6762-3.3336
143-0.87286-2.6821
144-1.4846-1.1367
1457.4904-0.23489
1464.78793.7658
147-4.27473.2979
1489.9077-1.1968
1490.052724-1.9294
1503.7988-4.9986
1512.270.2015
152-6.60235.4268
153-4.5217-0.95903
1541.8223-3.4418
1558.4789-2.9844
156-2.9323-2.3643
15712.837-3.8968
1583.7616-2.7767
1592.855-2.7453
160-3.2550.68182
16112.718-1.028
1621.2051-3.1592
163-2.67550.20394
1640.098573-1.4024
165-3.2196-0.67341
166-9.03382.4078
167-5.4064-0.89084
168-2.643-0.085169
169-6.62353.6729
170-11.3660.19606
1715.34951.9314
172-1.2245-2.8189
173-2.8601-1.641
174-1.8759-2.5613
1756.097-1.9248
1761.6418-2.5953
1779.24561.2292
178-0.412311.4617
179-3.0889-4.6986
180-6.5892-0.49829
181-10.104-0.35451
182-2.0224-3.4775
183-10.1592.2722
1848.4586-5.6184
185-3.0377-2.0998
1861.5154-2.8292
187-0.76584-3.3142
188-7.46543.1873
1892.7398-4.6092
1909.1371-5.3601
19110.6950.69171
192-5.4687-3.2311
193-4.3434-3.1151
1940.324832.1987
195-1.349-2.173
1961.0298-0.18794
197-3.2238-0.78166
19816.8722.487
199-2.5773-1.444
200-4.2323-2.798
2011.32313.9092
202-4.7228-2.4058
2033.1186-2.2875
2043.5268-2.7701
205-2.51322.9619
2064.387-0.61676
2070.371092.651
2080.80734-2.8945
209-1.47610.038621
210-7.13654.3047
211-3.05714.2905
212-1.3283-1.1415
2130.0833683.3319
214-6.70173.9635
21510.2221.9878
21612.2560.53641
21714.209-0.63164
2182.3013-1.291
219-4.73335.3711
2200.481659.8785
2211.6293-2.1536
22214.0533.4506
223-1.7853-3.4654
224-0.32474-3.0736
2255.6894-2.1599
226-0.018665-2.9448
2271.828-3.4131
2285.3271-1.1013
2290.364913.1079
230-1.3596-1.9167
231-4.98710.10323
2327.9561-2.2966
2330.22068-5.6637
234-6.94560.40904
235-3.6011-3.3702
2363.3272-0.26754
237-9.12141.0595
238-3.0362-1.1786
239-1.9998-4.1948
2402.69750.0085889
2410.58264-2.712
242-4.2343-3.7053
243-4.569-3.2128
244-2.9439-1.3019
245-8.50770.4229
24615.2062.433
2471.5214-1.2765
248-5.28872.6364
249-11.179-3.3634
250-3.50451.2103
251-6.3788-2.5205
2522.4284-5.7175
253-0.21567-0.92669
254-1.40030.32752
2553.2447-8.0207
2561.2815-4.9412
2572.9976-2.1884
258-3.86582.187
259-4.8357-2.1288
260-0.41568-1.8911
261-3.9849-0.71786
262-3.6683-1.2243
263-8.42814.0333
264-6.74183.8785
2653.5983-2.1065
266-0.32593-0.38884
26713.417-0.56855
26813.299-4.6703
269-1.3638-1.393
270-2.9155-4.6396
271-10.565-1.5589
272-1.4127-3.0361
273-2.8543-3.4521
274-3.1585-0.94263
275-1.2919-3.9222
276-0.44103-0.55848
2779.31410.50026
2781.18724.7934
279-1.9684-3.0854
2800.179791.8497
281-5.86632.268
2827.1208-1.2653
2830.47942-4.3415
2842.3032-0.93498
28514.3960.60317
286-6.45192.2351
287-5.6433-2.2899
288-5.4071-0.39292
289-2.0577-3.7766
2903.46313.2503
291-5.0894.2816
292-0.85477-3.0293
2931.77220.25607
2941.3141-5.2694
295-3.5665-2.6225
2960.85282-1.491
297-0.38391-1.2931
298-3.3045-3.0637
299-5.4484-1.214
30010.5042.0101
30112.7741.6553
3027.7891-2.3548
303-2.0681-4.0035
3042.3686-1.9378
305-6.89381.3444
306-10.2550.874
3079.16352.8149
308-3.8179-1.4829
3090.0071998-4.351
3103.0503-1.4251
3113.7798-1.6553
312-0.344020.91117
3134.1821-0.71874
3142.34612.161
3151.6462-3.2821
316-3.9141-3.7745
317-0.25228-5.6127
318-3.6486-2.9572
319-6.55040.42195
320-3.48811.9113
3210.30757-1.6775
3224.14413.4489
323-0.13702-2.0555
324-0.88608-1.2982
325-2.3707-0.8699
32613.5480.47986
3273.60320.31899
328-8.9026-1.6372
329-5.74234.7275
330-2.9649-3.7016
33119.5242.6239
332-5.53041.3068
333-6.3192.8702
334-0.096302-0.43852
335-3.03413.201
3367.7424-3.3691
33712.8762.182
3387.807-2.0018
3397.1251-1.3839
3402.146-2.9361
341-3.1579-3.3082
34212.8570.52637
343-4.46090.41499
344-3.8714-6.7903
3453.26662.4591
3466.2862-0.92647
347-1.3466-3.7478
3482.9247-1.9364
349-3.393-1.5449
350-4.5107-3.3019
351-5.2362-1.7177
3529.6689-1.5438
3530.32792-2.6098
354-9.3493-2.6134
355-5.04822.106
356-1.03262.3436
35715.8311.8268
358-5.31690.15211
359-7.08770.295
360-10.2251.5305
361-0.23111-0.95125
3628.4321.0287
363-12.672-1.1261
364-3.1958-0.3454
365-10.0552.9534
366-3.07760.044758
3673.39885.0924
368-10.3545.4431
369-4.09513.243
370-3.6014-2.2619
371-2.7905-1.6183
3728.44-2.519
3735.9782-2.0112
374-3.20770.90062
375-10.1792.081
376-1.2654-4.4711
37710.8490.39867
378-1.7256-1.6548
3791.17244.3994
380-0.781240.43168
3818.2328-1.3512
3824.26440.54162
383-6.6206-1.2762
3840.44188-0.1043
3853.5703-3.4004
386-2.8911-3.618
3870.38943-1.4637
388-1.83334.0067
3891.5069-3.0236
390-9.819-0.046123
3915.4231-2.8628
3922.427-2.1947
393-4.7515-2.8889
3946.3574-1.4319
3952.0153-1.4619
396-2.53150.75017
3971.4714-3.6837
3984.8453-0.29516
3996.209-1.1099
4002.6941-1.5908
40112.2731.7035
402-7.71374.069
403-5.2904-0.93495
404-4.16732.2126
4052.2915-3.6089
406-9.21861.2717
407-1.8882-4.2267
4083.4809-2.4008
409-15.9711.435
410-7.63923.8727
411-0.41989-2.7475
41215.2363.3721
4131.2279-3.3137
414-0.025314-0.30576
4151.4565-3.3996
4163.9208-5.0125
417-0.443420.34804
418-10.3125.6782
419-4.6918-0.72012
420-9.7617-2.4912
421-6.47965.35
4220.69094-0.56858
423-11.9375.0234
424-5.64312.9505
425-7.86032.6827
426-5.42584.7642
4276.8143-0.91464
4281.86720.53928
429-5.66873.8548
430-3.6841-0.7241
43112.8181.8647
432-7.91782.8577
43313.371.3791
4346.76920.19483
4358.76241.4099
436-4.24873.0242
437-0.267350.0756
438-1.1061-1.9569
43916.8162.3771
440-10.2981.9982
441-1.6096-2.32
442-0.172680.60164
443-1.4441-0.60782
44411.1811.3146
445-4.41840.12232
446-4.48252.675
4479.07243.0295
448-3.8057-0.96242
449-11.52-1.7201
4500.767671.8229
451-0.18758-1.3327
452-0.62047-4.5055
453-8.10696.5225
454-4.5074-1.3204
45510.236-2.2047
456-5.55250.00021899
4573.8245-2.2647
45810.5461.3206
4594.28930.36312
460-0.877250.14432
4618.3451-5.8887
4621.90730.63488
463-7.03652.51
464-2.89390.8411
465-2.58171.8505
466-4.74836.143
46710.3324.0206
468-3.50013.3277
469-4.74022.2181
470-6.7987-0.10113
471-5.7813-3.7013
472-0.60327-1.2424
47312.3041.3697
474-15.0743.3533
4752.67992.1341
4766.2944-0.2057
4775.22781.0546
478-7.16354.3811
479-12.373.9979
4809.90891.006
481-6.37665.3149
482-4.85664.4506
4833.72153.1037
484-0.60237-0.81353
48516.0732.4951
486-4.0583.7582
4874.6222-2.5753
488-3.0292-1.0614
489-3.03690.59289
490-1.84942.1436
491-1.9609-0.4637
4929.6623-2.8478
4935.6868-1.1324
4940.41864-1.7468
4950.52153-0.93077
4963.4212-3.0696
4974.3298-1.7452
498-3.2283-1.2798
499-4.39513.4549
50011.9193.4828
5011.3049-0.97267
502-2.29451.4826
5032.9239-0.11967
5044.3947-2.869
5053.3513-2.8925
5060.13762-2.2995
5071.55822.315
5080.44388-3.6573
5091.6934-3.4786
510-9.34450.75268
5111.6733-0.66872
5124.0386-1.3966
513-2.787-2.6906
514-7.86773.3261
515-10.094.6509
51610.1523.4358
51713.21.593
518-11.2344.1621
5197.1331-0.20658
520-3.852-0.60648
5212.6737-1.303
522-7.78350.28521
5231.2253-2.1468
524-7.5993-2.1465
5250.23982-2.6858
5265.7419-3.2073
527-3.3494-1.5173
528-0.032987-5.1049
5293.88254.2762
530-1.5161-3.0129
531-1.3866-1.8422
532-2.7270.35423
533-0.058996-2.415
534-4.7412-2.5324
53511.576-0.25308
5361.0766-6.6294
5378.09070.79008
538-2.6156-0.71192
539-4.4766-2.29
540-5.6003-2.0611
541-2.0655-4.3099
542-3.0757-3.4335
543-8.3551-1.8126
544-8.94353.5533
5455.2726-0.89376
546-8.7831-3.5542
5473.0878-4.4039
548-2.64531.6021
54910.1190.70335
5504.8648-3.1489
5511.51060.69477
552-4.4947-1.7247
553-2.91480.20685
554-1.73993.3005
555-4.94094.5968
556-3.3438-3.5136
557-0.27387-2.5161
55814.3661.3456
559-6.2491-0.40618
560-4.6627-1.1317
561-0.620814.363
5629.48631.423
56313.71.8097
564-7.80844.9654
565-0.252810.85259
566-0.99843.0504
5676.8596-1.7154
568-0.79709-2.8283
5691.7501-3.0115
570-8.39532.9481
571-1.48811.3684
5726.5701-1.7758
5732.4452-1.8534
574-0.77095-2.1316
575-5.61494.3594
5763.7738-4.6501
577-1.16-3.2986
578-0.91976-0.21772
5799.5467-1.2031
5804.9083-2.8096
581-4.91150.579
5826.0954-4.1509
583-6.93543.5332
584-6.7053-0.36214
585-2.07331.5966
586-13.677-3.0987
5876.0098-1.7164
5881.10860.13937
589-6.7263-0.081133

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: 61.4% (cumulative 61.4%)1PC2: 16.7% (cumulative 78.2%)2PC3: 7.2% (cumulative 85.4%)3PC4: 5.1% (cumulative 90.5%)4PC5: 3.4% (cumulative 93.9%)5PC6: 2.2% (cumulative 96.1%)6PC7: 0.9% (cumulative 97.0%)7PC8: 0.5% (cumulative 97.5%)8PC9: 0.4% (cumulative 97.9%)9PC10: 0.4% (cumulative 98.3%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
View explained variance values
Variance per displayed principal component
ComponentSpectral variance
PC161.44%
PC216.74%
PC37.24%
PC45.12%
PC53.39%
PC62.20%
PC70.88%
PC80.52%
PC90.43%
PC100.40%
X-Y spectral correlation 12

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

Spectral association with caco3_usda_a54_w_pct

Read Pearson correlation (−1 to +1) along the spectral axis (none); the solid curve shows |r| and the dashed curve shows signed r.

X_mir · caco3_usda_a54_w_pct spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,0004,000|r|signed raxis · Pearson correlation scale

Spectral association with cec_usda_a723_cmolc_kg

Read Pearson correlation (−1 to +1) along the spectral axis (none); the solid curve shows |r| and the dashed curve shows signed r.

X_mir · cec_usda_a723_cmolc_kg spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,0004,000|r|signed raxis · Pearson correlation scale

Spectral association with cf_usda_c236_w_pct

Read Pearson correlation (−1 to +1) along the spectral axis (none); the solid curve shows |r| and the dashed curve shows signed r.

X_mir · cf_usda_c236_w_pct spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,0004,000|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
caco3_usda_a54_w_pct0.7581,3100.1423.2%
cec_usda_a723_cmolc_kg0.5863,3480.37420.3%
cf_usda_c236_w_pct0.251,3920.1030.0%
clay_tot_usda_a334_w_pct0.5623,6520.1953.0%
k_ext_usda_a725_cmolc_kg0.3341,2100.1480.0%
n_tot_usda_a623_w_pct0.7562,9220.43145.0%
oc_usda_c729_w_pct0.7862,9200.42545.0%
p_ext_usda_a274_mg_kg0.1981,5560.0950.0%
ph_cacl2_usda_a481_index0.5991,3180.1732.5%
ph_h2o_usda_a268_index0.6161,3180.1822.7%
sand_tot_usda_c60_w_pct0.6571,1780.349.6%
silt_tot_usda_c62_w_pct0.5221,3840.232.6%

recovered_spectra

X_visnir · NIR · unknown

Read the signal and variation summaries for this source. Axis unit: none; 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.

recovered_spectra spectra0.00.20.40.601,0002,0003,000q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / none412none — median 0.1296 (q25–q75 0.1014–0.1604)428none — median 0.1207 (q25–q75 0.09274–0.151)442none — median 0.1217 (q25–q75 0.09179–0.1548)458none — median 0.1238 (q25–q75 0.09136–0.1596)474none — median 0.1258 (q25–q75 0.09227–0.1627)490none — median 0.1311 (q25–q75 0.09511–0.1699)504none — median 0.1392 (q25–q75 0.09898–0.1799)520none — median 0.1497 (q25–q75 0.1056–0.1965)536none — median 0.1619 (q25–q75 0.1143–0.2115)552none — median 0.1763 (q25–q75 0.1231–0.228)566none — median 0.1877 (q25–q75 0.1325–0.2419)582none — median 0.1976 (q25–q75 0.1409–0.2548)598none — median 0.2068 (q25–q75 0.1481–0.2664)612none — median 0.2149 (q25–q75 0.1546–0.2741)628none — median 0.2247 (q25–q75 0.1612–0.2826)644none — median 0.2331 (q25–q75 0.1682–0.2912)660none — median 0.2439 (q25–q75 0.1753–0.2987)674none — median 0.2519 (q25–q75 0.1824–0.3064)690none — median 0.2602 (q25–q75 0.1914–0.3157)706none — median 0.2684 (q25–q75 0.1973–0.3248)722none — median 0.276 (q25–q75 0.2053–0.3336)736none — median 0.283 (q25–q75 0.211–0.3396)752none — median 0.2902 (q25–q75 0.2174–0.3473)768none — median 0.2976 (q25–q75 0.2242–0.3552)784none — median 0.3034 (q25–q75 0.2297–0.3613)798none — median 0.3075 (q25–q75 0.2332–0.3659)814none — median 0.3118 (q25–q75 0.2366–0.3707)830none — median 0.3156 (q25–q75 0.2427–0.3744)844none — median 0.3174 (q25–q75 0.2477–0.3788)860none — median 0.3205 (q25–q75 0.2524–0.3808)876none — median 0.3237 (q25–q75 0.2555–0.3829)892none — median 0.3262 (q25–q75 0.2592–0.3845)906none — median 0.3278 (q25–q75 0.2618–0.3873)922none — median 0.3306 (q25–q75 0.266–0.3902)938none — median 0.3329 (q25–q75 0.269–0.3937)954none — median 0.3368 (q25–q75 0.2727–0.3973)968none — median 0.3384 (q25–q75 0.2765–0.4018)984none — median 0.3424 (q25–q75 0.281–0.4069)1,000none — median 0.3473 (q25–q75 0.2845–0.4103)1,016none — median 0.3498 (q25–q75 0.2882–0.4139)1,030none — median 0.3521 (q25–q75 0.2907–0.4168)1,046none — median 0.3558 (q25–q75 0.2953–0.4205)1,062none — median 0.3596 (q25–q75 0.2987–0.4243)1,076none — median 0.3616 (q25–q75 0.3015–0.4272)1,092none — median 0.3644 (q25–q75 0.3028–0.4305)1,108none — median 0.3675 (q25–q75 0.3075–0.4338)1,124none — median 0.3712 (q25–q75 0.3088–0.4363)1,138none — median 0.3738 (q25–q75 0.3102–0.4393)1,154none — median 0.3766 (q25–q75 0.3132–0.4425)1,170none — median 0.3801 (q25–q75 0.3165–0.4452)1,186none — median 0.384 (q25–q75 0.3182–0.4488)1,200none — median 0.3875 (q25–q75 0.3189–0.4519)1,216none — median 0.3907 (q25–q75 0.3218–0.4548)1,232none — median 0.393 (q25–q75 0.3257–0.4576)1,248none — median 0.3957 (q25–q75 0.3262–0.4602)1,262none — median 0.3989 (q25–q75 0.3281–0.4632)1,278none — median 0.4019 (q25–q75 0.3302–0.4655)1,294none — median 0.4036 (q25–q75 0.3321–0.4674)1,308none — median 0.4052 (q25–q75 0.3339–0.4699)1,324none — median 0.4073 (q25–q75 0.3357–0.472)1,340none — median 0.4086 (q25–q75 0.3373–0.4729)1,356none — median 0.4102 (q25–q75 0.339–0.476)1,370none — median 0.4096 (q25–q75 0.34–0.4755)1,386none — median 0.4037 (q25–q75 0.3386–0.4697)1,402none — median 0.3939 (q25–q75 0.3291–0.4581)1,418none — median 0.3908 (q25–q75 0.3262–0.4549)1,432none — median 0.3976 (q25–q75 0.3309–0.4638)1,448none — median 0.4022 (q25–q75 0.3354–0.4678)1,464none — median 0.4036 (q25–q75 0.338–0.4708)1,480none — median 0.4087 (q25–q75 0.3415–0.4753)1,494none — median 0.41 (q25–q75 0.3446–0.4774)1,510none — median 0.4145 (q25–q75 0.3465–0.4815)1,526none — median 0.4159 (q25–q75 0.3478–0.4858)1,542none — median 0.4176 (q25–q75 0.3496–0.4886)1,556none — median 0.4195 (q25–q75 0.3519–0.4912)1,572none — median 0.4214 (q25–q75 0.3529–0.4932)1,588none — median 0.4232 (q25–q75 0.3543–0.4949)1,602none — median 0.4245 (q25–q75 0.3552–0.4975)1,618none — median 0.4258 (q25–q75 0.3557–0.4981)1,634none — median 0.4272 (q25–q75 0.3568–0.4985)1,650none — median 0.428 (q25–q75 0.3577–0.4999)1,664none — median 0.4288 (q25–q75 0.3582–0.5018)1,680none — median 0.4293 (q25–q75 0.3588–0.5033)1,696none — median 0.4308 (q25–q75 0.3603–0.5049)1,712none — median 0.4309 (q25–q75 0.3608–0.5043)1,726none — median 0.4306 (q25–q75 0.3607–0.5027)1,742none — median 0.4306 (q25–q75 0.3616–0.5026)1,758none — median 0.4301 (q25–q75 0.3619–0.5019)1,774none — median 0.4297 (q25–q75 0.3626–0.5016)1,788none — median 0.4292 (q25–q75 0.3628–0.5009)1,804none — median 0.4298 (q25–q75 0.3636–0.5014)1,820none — median 0.4303 (q25–q75 0.3653–0.5031)1,834none — median 0.4311 (q25–q75 0.3659–0.5037)1,850none — median 0.4295 (q25–q75 0.3633–0.5008)1,866none — median 0.4252 (q25–q75 0.3594–0.4958)1,882none — median 0.4138 (q25–q75 0.3483–0.4795)1,896none — median 0.385 (q25–q75 0.3215–0.4522)1,912none — median 0.3587 (q25–q75 0.2957–0.4254)1,928none — median 0.3652 (q25–q75 0.2962–0.4296)1,944none — median 0.3706 (q25–q75 0.3022–0.4352)1,958none — median 0.3763 (q25–q75 0.3091–0.441)1,974none — median 0.3826 (q25–q75 0.317–0.4471)1,990none — median 0.39 (q25–q75 0.3261–0.4548)2,006none — median 0.3961 (q25–q75 0.3328–0.462)2,020none — median 0.4009 (q25–q75 0.3363–0.4667)2,036none — median 0.4043 (q25–q75 0.3405–0.4711)2,052none — median 0.4081 (q25–q75 0.3409–0.473)2,066none — median 0.409 (q25–q75 0.341–0.4749)2,082none — median 0.4097 (q25–q75 0.3426–0.4771)2,098none — median 0.4104 (q25–q75 0.3439–0.4766)2,114none — median 0.4107 (q25–q75 0.344–0.4771)2,128none — median 0.4113 (q25–q75 0.3444–0.4774)2,144none — median 0.4099 (q25–q75 0.3408–0.4755)2,160none — median 0.4041 (q25–q75 0.3406–0.4684)2,176none — median 0.3988 (q25–q75 0.3398–0.4629)2,190none — median 0.392 (q25–q75 0.3319–0.4544)2,206none — median 0.3832 (q25–q75 0.3242–0.4396)2,222none — median 0.3919 (q25–q75 0.3315–0.4557)2,238none — median 0.3966 (q25–q75 0.335–0.4609)2,252none — median 0.3951 (q25–q75 0.334–0.4611)2,268none — median 0.3961 (q25–q75 0.3326–0.4613)2,284none — median 0.3922 (q25–q75 0.3287–0.4572)2,298none — median 0.3877 (q25–q75 0.3246–0.4526)2,314none — median 0.3829 (q25–q75 0.3217–0.4461)2,330none — median 0.3782 (q25–q75 0.32–0.4381)2,346none — median 0.3715 (q25–q75 0.3153–0.4293)2,360none — median 0.3688 (q25–q75 0.3125–0.428)2,376none — median 0.3662 (q25–q75 0.3075–0.4265)2,392none — median 0.3625 (q25–q75 0.3041–0.4224)2,408none — median 0.3592 (q25–q75 0.3011–0.4187)2,422none — median 0.3549 (q25–q75 0.2934–0.4121)2,438none — median 0.3474 (q25–q75 0.2867–0.4055)2,454none — median 0.3404 (q25–q75 0.281–0.399)2,470none — median 0.3348 (q25–q75 0.2745–0.3926)2,484none — median 0.3297 (q25–q75 0.2688–0.3887)2,500none — median 0.3261 (q25–q75 0.2663–0.386)

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.
1,076
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
350–2,500 none
Mean spacing
?Average difference between adjacent spectral-axis coordinates; compare only within the same unit.
2 none
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.
589

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.
0.0333 – 0.694
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
0.125 – 0.431
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
0.3506
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
736.5
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
0.3061
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
6.0609e-06
Roughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR.
5.8e+04
Roughness S/N proxy dB
?20 log10 of the roughness signal-to-noise proxy. Units are decibels; compare only compatible signal representations.
1e+02 dB
Dynamic range
?Maximum minus minimum of the mean spectrum. Its magnitude depends on the signal representation.
0.306
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.
306

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.
2.32%
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.
37,063
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
5.86%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
11,513
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
1.82%
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.
0.20094
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.00016717
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.0010627
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
0.06621
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
0.16519
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.066865
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.14335
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
0.10637
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
0.48133
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
0.038151
Xcorr lag p95
?95th percentile of the absolute cross-correlation shift relative to the mean spectrum, in spectral channels.
0

Outliers & repeatability

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

PCA Q p95/median
?Q (squared prediction error) is variation left outside the retained PCA subspace. The displayed ratio compares its 95th percentile with its median.
4.3
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.
3.4
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.
1.8
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.
4
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		2.32%0.46mediumCorrupted 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		0.350631.00strongAtypical value: Too light / background visible or Too darkBackground, geometrymean(X finite)alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent
Overall amplitudeArea under curve
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit. Scoring: alert reuses baseline/shape drift because area scale depends on axis and units. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.area_under_curve		736.521.00strongAtypical value: Illumination difference or NormalProbe distancetrapezoid(mean_spectrum, spectral_axis)alert reuses baseline/shape drift because area scale depends on axis and units
Overall amplitudePeak-to-peak (PTP)
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum. Scoring: alert increases when dynamic range is abnormally flat. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.peak_to_peak		0.306070.00weakStrong 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		0.0147670.00weakNormal 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		6.0609e-060.00weakStableLamp, detectormedian MAD(second derivative) * 1.4826 / sqrt(6)alert = noise_rms / signal_scale, saturated at 5%
NoiseRoughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR. Scoring: alert decreases with SNR dB; >=40 dB is treated as low alert. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.roughness_signal_to_noise_proxy		578510.00weakGood 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		575.620.00weakReliable 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		37,0631.00strongArtifactsCosmic 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		5.86%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		11,5131.00strongDetector 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		1.82%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		0.000969%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		0.200941.00strongDriftIlluminationlinear 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		0.000167170.05weakSmoothBackground, 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		0.00106270.06weakFlatBiology or artifactmedian RMS(first derivative per spectrum)alert = d1_rms / signal_scale, saturated at 5%
Multivariate outliersPCA Q (SPE)
?Q (squared prediction error) is variation left outside the retained PCA subspace. The displayed ratio compares its 95th percentile with its median. Scoring: alert = min(1, pca_q_ratio / 8). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.pca_q_ratio		4.27170.53mediumAtypical 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		3.41710.43mediumExtreme 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		1.84850.46mediumGlobal 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		0.165191.00strongDifferent 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		0.143350.41weakSimilarBackground, geometryp95 spectral angle to dataset mean spectrumalert = min(1, SAM_p95 / 0.35 rad)
RepeatabilityRMS intra-ID
?Within-ID root mean square deviation from the group's mean spectrum, in signal units. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = RMS_intra_ID / signal_scale, saturated at 10%. Signal scale is the larger of the absolute mean level and absolute peak-to-peak range, with a floor of 1e-12. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.rms_intra_id		——not calculableNot enough information to score this metric on this dataset.Positioningmedian RMS distance to repeated-sample centroidalert = RMS_intra_ID / signal_scale, saturated at 10%
RepeatabilitySAM intra-ID
?Within-ID spectral angle to the group's mean spectrum, in radians. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = min(1, SAM_intra_ID / 0.15 rad). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.sam_intra_id		——not calculableNot enough information to score this metric on this dataset.Acquisitionmedian SAM to repeated-sample centroidalert = min(1, SAM_intra_ID / 0.15 rad)
RepeatabilityCV intra-ID
?Within-ID coefficient of variation: standard deviation relative to absolute mean; unstable near zero signal. Repeated IDs require documentation before this spread can be called technical repeatability. Scoring: alert = min(1, CV_intra_ID / 0.25). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
repeatability.cv_intra_id		——not calculableNot enough information to score this metric on this dataset.Operatormedian within-ID band CValert = min(1, CV_intra_ID / 0.25)
Structure of the datasetPCA score density
?Inverse median distance to nearby observations in retained PCA-score space. Larger raw values mean more closely spaced observations; scale depends on the PCA representation. The alert uses density variation, so raw density alone does not establish an anomaly. Scoring: alert follows density_cv/profile structure complexity, not raw density alone. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.pca_score_density		4.39780.85strongSubpopulationsDifferent batches1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure of the datasetkNN distance ratio (not LOF)
?95th percentile of mean k-nearest-neighbor distance divided by the population median of that distance, in PCA-score space. Values above 1 indicate an upper tail with more isolated observations; valid rare spectra can also be isolated. This distance ratio is not the Local Outlier Factor algorithm. Scoring: alert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.knn_distance_ratio_p95		2.54650.77strongIsolated 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		0.577810.85strongAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source recovered_spectra: 589 of 589 source observations are plotted. PC1 captures 91.5% and PC2 5.1% 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.

recovered_spectra PCA score plot-10-50510-3-2-1012PC1 3.26 · PC2 1.316PC1 3.238 · PC2 0.6614PC1 0.8284 · PC2 0.9716PC1 3.073 · PC2 0.4867PC1 -3.732 · PC2 -0.342PC1 -2.108 · PC2 0.4043PC1 -1.21 · PC2 0.4598PC1 3.653 · PC2 -0.5078PC1 -4.581 · PC2 -0.05012PC1 -3.921 · PC2 -0.08459PC1 -5.365 · PC2 0.6291PC1 1.557 · PC2 0.8203PC1 0.5066 · PC2 -0.1929PC1 4.656 · PC2 0.3386PC1 -0.7645 · PC2 -0.1346PC1 -1.01 · PC2 0.2014PC1 0.9571 · PC2 0.246PC1 -1.21 · PC2 0.9283PC1 -2.006 · PC2 0.1163PC1 1.061 · PC2 -0.05217PC1 0.1742 · PC2 0.3782PC1 -1.63 · PC2 -0.1758PC1 -1.886 · PC2 -0.3887PC1 2.103 · PC2 0.5552PC1 3.158 · PC2 -0.3595PC1 3.869 · PC2 -0.2021PC1 2.766 · PC2 -0.1183PC1 3.858 · PC2 0.455PC1 0.2566 · PC2 0.9391PC1 -2.016 · PC2 0.2958PC1 -3.585 · PC2 -0.7445PC1 3.525 · PC2 1.077PC1 5.306 · PC2 0.0894PC1 3.956 · PC2 -0.7824PC1 -3.469 · PC2 0.7322PC1 1.061 · PC2 0.1601PC1 5.947 · PC2 0.5754PC1 -0.7951 · PC2 1.157PC1 -2.494 · PC2 0.706PC1 1.952 · PC2 -0.001926PC1 -7.187 · PC2 0.6537PC1 1.556 · PC2 0.1369PC1 2.877 · PC2 -0.565PC1 -0.9981 · PC2 -1.496PC1 -1.061 · PC2 -1.952e-05PC1 2.727 · PC2 0.04115PC1 0.5877 · PC2 -0.4896PC1 0.9525 · PC2 -0.421PC1 7.073 · PC2 0.325PC1 -4.502 · PC2 0.03241PC1 0.282 · PC2 0.5802PC1 0.7779 · PC2 0.9771PC1 -3.277 · PC2 0.9827PC1 -1.925 · PC2 -0.5163PC1 -2.185 · PC2 -1.291PC1 3.106 · PC2 0.8496PC1 -2.968 · PC2 0.8139PC1 -6.274 · PC2 0.1698PC1 2.851 · PC2 0.6308PC1 0.4647 · PC2 1.021PC1 -0.3448 · PC2 -1.193PC1 0.5211 · PC2 1.045PC1 -3.134 · PC2 0.9391PC1 -0.3444 · PC2 0.2478PC1 3.194 · PC2 0.2792PC1 -5.34 · PC2 -0.3889PC1 -2.856 · PC2 -0.4757PC1 1.33 · PC2 -0.6068PC1 1.884 · PC2 -0.4626PC1 -0.297 · PC2 -0.04064PC1 2.49 · PC2 -0.08797PC1 -0.9607 · PC2 -0.6603PC1 -2.253 · PC2 -0.08046PC1 1.579 · PC2 -1.731PC1 -0.9786 · PC2 -1.454PC1 2.363 · PC2 -0.8858PC1 -0.6452 · PC2 1.01PC1 3.466 · PC2 0.852PC1 1.446 · PC2 -0.4708PC1 -0.446 · PC2 0.6196PC1 3.554 · PC2 0.4676PC1 -4.159 · PC2 1.15PC1 0.9852 · PC2 -1.026PC1 3.186 · PC2 0.4062PC1 2.617 · PC2 -0.1167PC1 -6.095 · PC2 0.8691PC1 0.1508 · PC2 0.05539PC1 -1.704 · PC2 -0.9962PC1 1.839 · PC2 -0.05142PC1 -0.9636 · PC2 -0.1868PC1 -1.352 · PC2 -0.4705PC1 2.721 · PC2 -0.634PC1 -3.148 · PC2 -0.8418PC1 -2.081 · PC2 -0.3326PC1 1.887 · PC2 1.145PC1 -3.378 · PC2 -0.1487PC1 -0.5256 · PC2 0.07727PC1 -1.373 · PC2 0.7126PC1 0.3852 · PC2 -1.125PC1 -0.4631 · PC2 0.1994PC1 -1.73 · PC2 0.4619PC1 0.2177 · PC2 -0.1822PC1 -3.462 · PC2 -0.6056PC1 0.4492 · PC2 0.3799PC1 -0.432 · PC2 0.8744PC1 -0.2243 · PC2 -0.7964PC1 4.589 · PC2 -0.2114PC1 0.375 · PC2 0.02276PC1 2.197 · PC2 0.6777PC1 0.8016 · PC2 -0.2037PC1 1.793 · PC2 -0.1532PC1 2.094 · PC2 -0.7141PC1 -4.171 · PC2 0.8833PC1 -2.089 · PC2 0.01822PC1 -0.7243 · PC2 -0.5986PC1 -1.657 · PC2 -0.1601PC1 3.014 · PC2 -0.08282PC1 -2.149 · PC2 -0.01854PC1 -2.344 · PC2 -0.772PC1 3.64 · PC2 0.538PC1 0.09861 · PC2 -0.786PC1 6.611 · PC2 0.2591PC1 2.131 · PC2 -0.5098PC1 0.2395 · PC2 0.33PC1 1.815 · PC2 0.4479PC1 -2.47 · PC2 0.823PC1 2.111 · PC2 0.3945PC1 -1.002 · PC2 -0.1427PC1 -4.108 · PC2 -0.4955PC1 -2.873 · PC2 -1.744PC1 -1.822 · PC2 -0.6338PC1 2.571 · PC2 -0.4537PC1 0.6142 · PC2 0.9594PC1 0.3708 · PC2 -1.093PC1 -1.859 · PC2 -0.8124PC1 -1.783 · PC2 -0.04637PC1 -0.337 · PC2 0.06613PC1 -2.546 · PC2 1.037PC1 -3.835 · PC2 0.2814PC1 1.491 · PC2 -0.1173PC1 -0.7706 · PC2 -0.2082PC1 -1.028 · PC2 -2.108PC1 -0.221 · PC2 0.1834PC1 2.091 · PC2 -0.6719PC1 0.8267 · PC2 0.4358PC1 1 · PC2 0.2021PC1 -3.162 · PC2 -1.187PC1 -2.339 · PC2 0.6988PC1 -1.464 · PC2 -1.199PC1 3.238 · PC2 0.8414PC1 -0.3112 · PC2 0.2929PC1 -4.624 · PC2 -0.6372PC1 2.456 · PC2 -0.4121PC1 0.01373 · PC2 -1.213PC1 1.68 · PC2 0.1301PC1 3.227 · PC2 0.1936PC1 -3.658 · PC2 0.7604PC1 -1.355 · PC2 -0.5487PC1 0.6461 · PC2 -0.5916PC1 2.154 · PC2 -0.396PC1 -2.26 · PC2 0.7349PC1 1.59 · PC2 0.6407PC1 0.8605 · PC2 -0.09116PC1 4.934 · PC2 0.03956PC1 0.4297 · PC2 -0.7038PC1 1.535 · PC2 1.26PC1 1.365 · PC2 -0.5074PC1 2.414 · PC2 0.2046PC1 -0.6586 · PC2 0.0425PC1 1.757 · PC2 -0.9754PC1 3.515 · PC2 -1.414PC1 2.902 · PC2 0.07618PC1 0.6113 · PC2 -0.7477PC1 3.274 · PC2 0.291PC1 -1.579 · PC2 1.063PC1 0.9972 · PC2 0.8737PC1 -3.511 · PC2 -0.2112PC1 2.488 · PC2 0.1647PC1 2.591 · PC2 -0.3557PC1 3.054 · PC2 -0.1668PC1 0.6341 · PC2 0.819PC1 2.51 · PC2 0.2775PC1 -0.01824 · PC2 -0.178PC1 -2.532 · PC2 0.9545PC1 -1.886 · PC2 -0.2662PC1 -2.323 · PC2 1.449PC1 1.55 · PC2 0.2916PC1 3.013 · PC2 -0.4565PC1 2.336 · PC2 0.5552PC1 -3.967 · PC2 1.024PC1 -4.797 · PC2 -0.4166PC1 2.86 · PC2 -1.014PC1 1.274 · PC2 0.09227PC1 0.3506 · PC2 -0.2945PC1 4.312 · PC2 -0.6661PC1 0.7253 · PC2 0.5289PC1 1.59 · PC2 -1.222PC1 1.473 · PC2 -1.083PC1 1.203 · PC2 0.2423PC1 0.6543 · PC2 -1.417PC1 -6.492 · PC2 1.387PC1 2.601 · PC2 -0.3528PC1 -2.038 · PC2 0.5371PC1 1.948 · PC2 -0.7435PC1 3.295 · PC2 -0.4223PC1 2.323 · PC2 -0.2559PC1 1.589 · PC2 0.3558PC1 4.02 · PC2 0.4177PC1 3.693 · PC2 -0.423PC1 -2.039 · PC2 -0.5237PC1 1.834 · PC2 -0.6932PC1 0.4957 · PC2 0.03025PC1 -0.07222 · PC2 -0.2475PC1 -4.105 · PC2 -0.905PC1 -5.702 · PC2 -0.1473PC1 -1.534 · PC2 -0.2885PC1 -4.782 · PC2 0.9649PC1 1.474 · PC2 0.6037PC1 -2.961 · PC2 -0.07462PC1 -0.04322 · PC2 -0.1634PC1 0.7313 · PC2 0.8697PC1 -4.549 · PC2 -0.007082PC1 -0.1644 · PC2 -0.1805PC1 -0.4757 · PC2 0.4542PC1 -0.03161 · PC2 0.4686PC1 4.074 · PC2 -0.4268PC1 3.459 · PC2 0.4621PC1 -1.718 · PC2 0.7756PC1 0.6175 · PC2 0.4599PC1 4.407 · PC2 0.6675PC1 3.881 · PC2 0.5004PC1 0.8041 · PC2 0.4151PC1 -2.455 · PC2 -0.3522PC1 -0.8407 · PC2 -0.3182PC1 1.459 · PC2 0.2103PC1 0.3688 · PC2 -0.4649PC1 1.922 · PC2 -0.3616PC1 4.103 · PC2 0.03025PC1 0.9426 · PC2 -0.02115PC1 0.3397 · PC2 0.2593PC1 4.088 · PC2 0.3991PC1 2.572 · PC2 -0.3801PC1 -0.1321 · PC2 1.032PC1 -0.4149 · PC2 0.3459PC1 3.567 · PC2 -0.4126PC1 -3.185 · PC2 -0.6309PC1 3.089 · PC2 0.4638PC1 -1.352 · PC2 -0.3584PC1 3.972 · PC2 1.082PC1 -3.614 · PC2 0.4451PC1 3.752 · PC2 -0.1579PC1 -2.19 · PC2 1.069PC1 -2.511 · PC2 1.364PC1 3.413 · PC2 -0.2814PC1 -3.828 · PC2 1.219PC1 1.187 · PC2 0.3469PC1 6.713 · PC2 0.5797PC1 -3.637 · PC2 0.204PC1 -2.167 · PC2 -0.694PC1 -0.315 · PC2 0.6656PC1 2.735 · PC2 0.352PC1 -1.617 · PC2 -0.4444PC1 -1.588 · PC2 -1.001PC1 -1.309 · PC2 -0.9661PC1 -2.118 · PC2 -0.4662PC1 3.919 · PC2 -0.9289PC1 -0.5104 · PC2 -0.2089PC1 -0.9808 · PC2 0.9445PC1 2.826 · PC2 0.201PC1 -1.033 · PC2 -0.1979PC1 3.489 · PC2 0.4519PC1 2.665 · PC2 -0.584PC1 0.2354 · PC2 0.07811PC1 2.202 · PC2 0.004049PC1 0.5314 · PC2 0.5185PC1 0.03879 · PC2 -0.1887PC1 -2.458 · PC2 -0.2491PC1 -6.027 · PC2 0.1255PC1 -1.915 · PC2 -0.6893PC1 -1.178 · PC2 -1.298PC1 2.91 · PC2 -0.05357PC1 -2.291 · PC2 0.3436PC1 1.535 · PC2 0.331PC1 0.6705 · PC2 -0.1887PC1 0.4995 · PC2 -0.936PC1 -1.125 · PC2 -0.4228PC1 3.792 · PC2 -0.2639PC1 2.924 · PC2 -0.9765PC1 1.036 · PC2 0.3364PC1 -4.471 · PC2 -0.06765PC1 -0.3793 · PC2 -0.6821PC1 -1.064 · PC2 -0.6642PC1 0.7384 · PC2 0.01556PC1 -0.7792 · PC2 -0.07437PC1 0.9579 · PC2 -0.8335PC1 2.203 · PC2 -0.3794PC1 3.715 · PC2 0.4553PC1 1.069 · PC2 -0.7247PC1 1.354 · PC2 -0.9269PC1 -6.822 · PC2 -0.2894PC1 -4.922 · PC2 -0.4222PC1 -2.387 · PC2 -0.7429PC1 3.862 · PC2 -0.7743PC1 -3.992 · PC2 0.7232PC1 -2.158 · PC2 0.9534PC1 2.02 · PC2 -0.1551PC1 -6.388 · PC2 -0.01573PC1 2.102 · PC2 -0.003135PC1 1.406 · PC2 0.5947PC1 0.4062 · PC2 0.2452PC1 0.1425 · PC2 0.4374PC1 2.19 · PC2 1.029PC1 -1.761 · PC2 0.1797PC1 -3.049 · PC2 0.4285PC1 -3.22 · PC2 0.5521PC1 4.491 · PC2 0.4037PC1 -2.144 · PC2 -0.2469PC1 0.8609 · PC2 0.8042PC1 3.749 · PC2 0.2501PC1 3.381 · PC2 0.6974PC1 -2.396 · PC2 0.7495PC1 -2.519 · PC2 -1.26PC1 5.409 · PC2 0.07866PC1 1.364 · PC2 0.6129PC1 0.3816 · PC2 0.7552PC1 -1.325 · PC2 0.05409PC1 -1.434 · PC2 0.555PC1 3.427 · PC2 -0.5009PC1 -2.549 · PC2 -0.1865PC1 4.1 · PC2 0.1339PC1 -3.455 · PC2 -0.7438PC1 4.646 · PC2 1.02PC1 -0.8512 · PC2 -0.5076PC1 3.677 · PC2 -0.2933PC1 1.784 · PC2 -0.4427PC1 -1.138 · PC2 0.8182PC1 -4.649 · PC2 -0.3268PC1 2.473 · PC2 -0.007839PC1 -4.045 · PC2 1.327PC1 2.159 · PC2 0.1549PC1 5.179 · PC2 0.3519PC1 -1.257 · PC2 -1.087PC1 0.04825 · PC2 0.4068PC1 5.527 · PC2 -1.519PC1 0.165 · PC2 -0.6385PC1 2.335 · PC2 0.5285PC1 4.684 · PC2 0.07942PC1 -1.872 · PC2 0.8892PC1 1.302 · PC2 0.5451PC1 5.019 · PC2 -1.039PC1 2.126 · PC2 -0.2107PC1 -0.4983 · PC2 -0.7646PC1 -0.8232 · PC2 1.221PC1 -1.721 · PC2 0.07588PC1 -0.4097 · PC2 0.7372PC1 -1.954 · PC2 -0.6034PC1 -1.181 · PC2 -0.9323PC1 1.784 · PC2 1.3PC1 4.446 · PC2 -0.6435PC1 -0.4048 · PC2 1.329PC1 -0.185 · PC2 1.249PC1 -5.533 · PC2 0.2436PC1 4.802 · PC2 -0.8362PC1 2.628 · PC2 0.4244PC1 4.542 · PC2 0.4085PC1 1.138 · PC2 0.3053PC1 -2.323 · PC2 -1.045PC1 -3.959 · PC2 -0.07608PC1 -6.874 · PC2 -0.3723PC1 3.479 · PC2 -0.6238PC1 1.277 · PC2 -0.267PC1 1.729 · PC2 0.5182PC1 -1.788 · PC2 1.762PC1 0.7747 · PC2 -0.2948PC1 3.912 · PC2 -0.5189PC1 -7.542 · PC2 0.872PC1 -2.922 · PC2 -0.8735PC1 3.932 · PC2 -0.02151PC1 -4.922 · PC2 0.05861PC1 2.329 · PC2 0.4038PC1 -2.595 · PC2 0.09862PC1 0.02013 · PC2 -0.1569PC1 3.938 · PC2 1.098PC1 -3.618 · PC2 0.644PC1 -1.958 · PC2 0.5403PC1 5.202 · PC2 0.6419PC1 -2.2 · PC2 1.497PC1 -3.501 · PC2 -0.602PC1 1.91 · PC2 0.5507PC1 -0.698 · PC2 -0.2487PC1 -3.268 · PC2 0.5131PC1 3.339 · PC2 0.0356PC1 1.232 · PC2 0.551PC1 -0.7472 · PC2 0.2838PC1 -1.848 · PC2 1.397PC1 2.742 · PC2 -0.1979PC1 0.1468 · PC2 0.1743PC1 0.4147 · PC2 0.2942PC1 0.7152 · PC2 0.1591PC1 0.6264 · PC2 0.04646PC1 -3.342 · PC2 -0.5317PC1 0.2214 · PC2 -0.6015PC1 2.23 · PC2 0.9242PC1 -1.824 · PC2 -0.69PC1 -1.209 · PC2 0.2591PC1 1.184 · PC2 -0.2089PC1 1.594 · PC2 0.3384PC1 4.882 · PC2 0.8419PC1 2.002 · PC2 -0.8973PC1 -2.037 · PC2 -1.262PC1 1.175 · PC2 -0.3835PC1 -9.061 · PC2 0.3512PC1 -3.357 · PC2 0.4718PC1 2.448 · PC2 0.2434PC1 -1.698 · PC2 -0.1466PC1 -1.009 · PC2 0.5101PC1 1.555 · PC2 -0.2289PC1 -3.646 · PC2 -0.007573PC1 -1.566 · PC2 0.1459PC1 3.285 · PC2 0.1193PC1 -3.911 · PC2 -0.2468PC1 -2.199 · PC2 1.584PC1 -4.462 · PC2 -0.1035PC1 -0.2936 · PC2 0.8138PC1 -0.1803 · PC2 1.122PC1 -5.814 · PC2 0.02624PC1 -0.8945 · PC2 0.2317PC1 -1.376 · PC2 -0.1368PC1 -0.4571 · PC2 -0.547PC1 1.058 · PC2 0.9481PC1 -4.964 · PC2 -0.3752PC1 1.767 · PC2 -0.09107PC1 -1.768 · PC2 -1.179PC1 -0.0322 · PC2 -0.28PC1 -7.845 · PC2 0.761PC1 5.528 · PC2 0.5864PC1 -0.7658 · PC2 -1.725PC1 7.698 · PC2 0.7958PC1 -6.89 · PC2 -0.07444PC1 3.543 · PC2 -0.4067PC1 -0.04945 · PC2 0.3144PC1 1.388 · PC2 0.8963PC1 -0.08091 · PC2 1.241PC1 -2.767 · PC2 0.949PC1 -1.456 · PC2 -0.3714PC1 -2.795 · PC2 -0.2828PC1 0.2209 · PC2 -0.5567PC1 1.604 · PC2 -0.1637PC1 7.652 · PC2 0.9841PC1 -3.735 · PC2 -0.6151PC1 0.02483 · PC2 1.202PC1 2.188 · PC2 0.2863PC1 -3.008 · PC2 0.05369PC1 -0.6327 · PC2 0.9879PC1 -0.5674 · PC2 0.3589PC1 -0.4182 · PC2 -0.5954PC1 3.057 · PC2 0.2368PC1 -4.946 · PC2 -0.443PC1 1.334 · PC2 -0.03038PC1 -4.95 · PC2 1.198PC1 0.113 · PC2 0.6224PC1 -1.634 · PC2 0.07837PC1 1.097 · PC2 -0.4576PC1 -1.601 · PC2 0.1439PC1 3.645 · PC2 -1.229PC1 -2.748 · PC2 -0.6561PC1 -4.054 · PC2 0.01973PC1 -3.276 · PC2 -0.9297PC1 -0.9445 · PC2 -0.7861PC1 0.6454 · PC2 -1.032PC1 3.526 · PC2 -1.449PC1 4.377 · PC2 -0.434PC1 -3.478 · PC2 -0.6889PC1 1.374 · PC2 0.3964PC1 -0.7541 · PC2 0.3513PC1 -0.1112 · PC2 0.9282PC1 0.1609 · PC2 -1.015PC1 -3.757 · PC2 -0.2621PC1 -4.981 · PC2 -0.2345PC1 -1.938 · PC2 0.4716PC1 -3.476 · PC2 -0.5109PC1 0.4256 · PC2 -0.4171PC1 2.202 · PC2 -0.1524PC1 0.9011 · PC2 -0.5494PC1 -1.947 · PC2 -0.2521PC1 -4.68 · PC2 -1.057PC1 -0.7586 · PC2 -0.4027PC1 3.528 · PC2 -0.7251PC1 -0.3262 · PC2 -1.218PC1 -4.326 · PC2 -0.5342PC1 0.1842 · PC2 0.6346PC1 -1.428 · PC2 -0.2084PC1 1.456 · PC2 -0.2641PC1 -0.9629 · PC2 1.286PC1 1.69 · PC2 -0.1167PC1 -3.343 · PC2 0.05357PC1 1.295 · PC2 0.4236PC1 -3.64 · PC2 0.348PC1 -1.536 · PC2 -0.5848PC1 -0.2726 · PC2 -0.5455PC1 -5.922 · PC2 0.7091PC1 -3.336 · PC2 -1.154PC1 -1.727 · PC2 -0.2247PC1 -2.901 · PC2 0.2809PC1 2.578 · PC2 0.7884PC1 1.356 · PC2 0.4488PC1 1.51 · PC2 -0.1534PC1 2.298 · PC2 -0.6945PC1 -0.4671 · PC2 0.05636PC1 3.997 · PC2 0.7745PC1 -2.2 · PC2 -0.8574PC1 -0.4043 · PC2 -1.174PC1 1.098 · PC2 0.9331PC1 -0.4855 · PC2 -0.07434PC1 -0.8919 · PC2 -0.8005PC1 -0.05529 · PC2 -1.005PC1 -5.07 · PC2 -0.5044PC1 0.9306 · PC2 -1.137PC1 -0.6353 · PC2 -0.9667PC1 2.219 · PC2 -0.6928PC1 0.4962 · PC2 1.027PC1 3.976 · PC2 0.3009PC1 0.9281 · PC2 0.4939PC1 3.217 · PC2 -0.6965PC1 3.322 · PC2 0.5PC1 -2.522 · PC2 0.8741PC1 2.465 · PC2 0.3545PC1 0.9035 · PC2 -0.4508PC1 -0.3578 · PC2 -0.08093PC1 3.903 · PC2 0.1446PC1 1.756 · PC2 -0.7393PC1 -0.9737 · PC2 -0.5351PC1 -0.7128 · PC2 1.365PC1 5.004 · PC2 -0.2065PC1 -2.871 · PC2 1.212PC1 -3.04 · PC2 0.1149PC1 0.6016 · PC2 -0.2792PC1 -2.05 · PC2 0.1136PC1 1.786 · PC2 -0.2414PC1 3.295 · PC2 -0.6858PC1 3.341 · PC2 -0.5995PC1 -0.1999 · PC2 -0.8468PC1 3.194 · PC2 0.3857PC1 -0.8308 · PC2 -0.4037PC1 0.8258 · PC2 -1.589PC1 5.361 · PC2 0.7634PC1 -3.783 · PC2 0.36PC1 1.489 · PC2 -0.3236PC1 -3.727 · PC2 -0.5239PC1 -4.457 · PC2 1.141PC1 1.194 · PC2 -0.3202PC1 1.122 · PC2 -0.3352PC1 5.603 · PC2 0.1079PC1 -5.914 · PC2 -0.2796PC1 -4.345 · PC2 -0.5659PC1 0.7052 · PC2 -0.68PC1 -0.5883 · PC2 -0.247PC1 -2.044 · PC2 -0.4007PC1 1.192 · PC2 0.7609PC1 -2.545 · PC2 1.194PC1 -6.389 · PC2 0.1948PC1 -3.34 · PC2 -0.9698PC1 -1.395 · PC2 -0.7PC1 -1.342 · PC2 -0.5421PC1 2.962 · PC2 -0.1595PC1 -0.4295 · PC2 -0.5345PC1 -2.937 · PC2 -0.2184PC1 -0.5551 · PC2 0.6612PC1 -0.8966 · PC2 1.109PC1 -2.913 · PC2 -0.02826PC1 -1.982 · PC2 -1.153PC1 1.889 · PC2 0.3482PC1 -0.1872 · PC2 -0.1356PC1 0.7608 · PC2 0.3484PC1 1.947 · PC2 -0.01647PC1 -2.328 · PC2 -0.1152PC1 4.277 · PC2 -0.3656PC1 0.06081 · PC2 0.3502PC1 -0.5612 · PC2 0.2219PC1 -2.873 · PC2 1.008PC1 0.4688 · PC2 -0.495PC1 1.533 · PC2 0.3266PC1 -0.03032 · PC2 -0.3507PC1 -0.2326 · PC2 -0.7015PC1 -0.6078 · PC2 -0.8621PC1 5.381 · PC2 0.1605PC1 -0.1308 · PC2 0.2724PC1 -1.815 · PC2 -0.645PC1 -1.323 · PC2 -0.9565PC1 (91.5%)PC2 (5.1%)589 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
13.25961.3163
23.23830.66138
30.82840.97163
43.07330.48667
5-3.7325-0.342
6-2.10760.40429
7-1.21020.45977
83.6535-0.50782
9-4.5806-0.050124
10-3.9208-0.08459
11-5.36530.62911
121.55660.82033
130.50662-0.19289
144.65610.33857
15-0.76448-0.13462
16-1.01040.20137
170.957140.24602
18-1.20950.92833
19-2.00640.11628
201.0614-0.05217
210.174220.37822
22-1.63-0.17581
23-1.8859-0.38873
242.10330.55517
253.1583-0.35951
263.8688-0.20206
272.7665-0.11827
283.85770.45502
290.256620.93914
30-2.01640.29579
31-3.585-0.74447
323.5251.0772
335.3060.089398
343.9555-0.78243
35-3.46910.7322
361.06120.16013
375.94660.57543
38-0.795111.1567
39-2.49440.706
401.9524-0.0019256
41-7.18680.65374
421.55580.13687
432.8769-0.56504
44-0.99807-1.4964
45-1.061-1.9517e-05
462.72670.04115
470.58768-0.48957
480.95248-0.42098
497.07270.32503
50-4.50170.032413
510.282040.58015
520.777940.97707
53-3.27730.9827
54-1.9252-0.51629
55-2.1852-1.2911
563.10590.84961
57-2.96760.81388
58-6.27390.16978
592.85140.63079
600.46471.0214
61-0.34481-1.1934
620.521121.0449
63-3.13370.93914
64-0.344410.24781
653.19420.27917
66-5.3401-0.38891
67-2.8557-0.47567
681.3296-0.60682
691.884-0.46255
70-0.29698-0.040644
712.49-0.08797
72-0.96069-0.66027
73-2.2533-0.080458
741.5792-1.7306
75-0.97859-1.4544
762.3627-0.88576
77-0.645251.0098
783.46560.85195
791.4459-0.47079
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1940.35063-0.29454
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1960.725260.52885
1971.5903-1.2223
1981.4735-1.083
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321-2.39570.74946
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373-1.78781.7618
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379-4.9220.05861
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384-3.61790.64403
385-1.95810.54027
3865.2020.6419
387-2.21.4972
388-3.501-0.60202
3891.90960.55073
390-0.69799-0.24873
391-3.26790.51312
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395-1.84811.3968
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3990.715230.15908
4000.626450.046455
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405-1.20950.25906
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410-2.0375-1.2624
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413-3.35660.47182
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415-1.6977-0.14662
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418-3.6462-0.0075735
419-1.56650.14594
4203.28550.11928
421-3.9115-0.24683
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423-4.462-0.10348
424-0.29360.81378
425-0.180291.1217
426-5.81420.02624
427-0.894540.23165
428-1.3765-0.13681
429-0.45715-0.54698
4301.05790.94807
431-4.964-0.37521
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433-1.7679-1.1794
434-0.032199-0.27995
435-7.84540.76099
4365.52780.58635
437-0.76577-1.7253
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439-6.8896-0.074435
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441-0.049450.31436
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443-0.0809131.2412
444-2.7670.94897
445-1.4563-0.37143
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4470.22086-0.55675
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4497.65190.98408
450-3.7354-0.61506
4510.0248271.2022
4522.18840.28627
453-3.00760.053689
454-0.632670.98791
455-0.567370.35889
456-0.41816-0.59538
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458-4.9459-0.44296
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460-4.94961.1983
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462-1.63450.078374
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464-1.60130.1439
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4700.64536-1.0321
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473-3.478-0.68891
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475-0.75410.3513
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479-4.9806-0.23452
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492-1.4278-0.20836
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501-5.92210.70906
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509-0.467060.056361
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511-2.2005-0.85735
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526-2.52160.87414
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529-0.35777-0.080926
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585-0.6078-0.8621
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587-0.130820.27239
588-1.8146-0.64497
589-1.3231-0.95648

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: 91.5% (cumulative 91.5%)1PC2: 5.1% (cumulative 96.6%)2PC3: 2.1% (cumulative 98.7%)3PC4: 0.7% (cumulative 99.4%)4PC5: 0.3% (cumulative 99.7%)5PC6: 0.2% (cumulative 99.8%)6PC7: 0.1% (cumulative 99.9%)7PC8: 0.0% (cumulative 99.9%)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
PC191.46%
PC25.13%
PC32.08%
PC40.72%
PC50.29%
PC60.16%
PC70.05%
PC80.04%
PC90.01%
PC100.01%
X-Y spectral correlation 12

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

Spectral association with caco3_usda_a54_w_pct

Read Pearson correlation (−1 to +1) along the spectral axis (none); the solid curve shows |r| and the dashed curve shows signed r.

X_visnir · caco3_usda_a54_w_pct spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale

Spectral association with cec_usda_a723_cmolc_kg

Read Pearson correlation (−1 to +1) along the spectral axis (none); the solid curve shows |r| and the dashed curve shows signed r.

X_visnir · cec_usda_a723_cmolc_kg spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale

Spectral association with cf_usda_c236_w_pct

Read Pearson correlation (−1 to +1) along the spectral axis (none); the solid curve shows |r| and the dashed curve shows signed r.

X_visnir · cf_usda_c236_w_pct spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
caco3_usda_a54_w_pct0.4574560.3390.0%
cec_usda_a723_cmolc_kg0.4852,5000.3710.0%
cf_usda_c236_w_pct0.1111,6540.08230.0%
clay_tot_usda_a334_w_pct0.3325700.1520.0%
k_ext_usda_a725_cmolc_kg0.1542,5000.05610.0%
n_tot_usda_a623_w_pct0.5336380.41510.1%
oc_usda_c729_w_pct0.5156140.3725.7%
p_ext_usda_a274_mg_kg0.2386800.210.0%
ph_cacl2_usda_a481_index0.2115540.08860.0%
ph_h2o_usda_a268_index0.2595580.1360.0%
sand_tot_usda_c60_w_pct0.2135500.1050.0%
silt_tot_usda_c62_w_pct0.5966100.45824.2%

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

4 experimental metadata fields (M) · 12 informative targets (Y).

VariableRoleDistinct valuesCompleteRange / balance
instrument_modelM2100%IR 1
scan_model_codeM2100%IR 1
longitudeM589100%-9.153 – 30.97
latitudeM589100%36.8 – 69.25
caco3_usda_a54_w_pctY138100%0 – 66.9
cec_usda_a723_cmolc_kgY314100%1 – 193.1
cf_usda_c236_w_pctY53100%0 – 65
clay_tot_usda_a334_w_pctY71100%0 – 79
k_ext_usda_a725_cmolc_kgY549100%0 – 37.56
n_tot_usda_a623_w_pctY106100%0 – 3.34
oc_usda_c729_w_pctY369100%0.1 – 53.42
p_ext_usda_a274_mg_kgY274100%0 – 288
ph_cacl2_usda_a481_indexY316100%2.85 – 7.84
ph_h2o_usda_a268_indexY336100%3.55 – 8.55
sand_tot_usda_c60_w_pctY97100%0 – 98
silt_tot_usda_c62_w_pctY77100%0 – 83

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 12

caco3_usda_a54_w_pct

target · numeric

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

caco3_usda_a54_w_pct distribution05001,0000 – 2.788: 9002.788 – 5.575: 325.575 – 8.363: 448.363 – 11.15: 2811.15 – 13.94: 2813.94 – 16.73: 1816.73 – 19.51: 2019.51 – 22.3: 1222.3 – 25.09: 1825.09 – 27.88: 1627.88 – 30.66: 1630.66 – 33.45: 633.45 – 36.24: 636.24 – 39.02: 439.02 – 41.81: 841.81 – 44.6: 444.6 – 47.39: 247.39 – 50.18: 450.18 – 52.96: 452.96 – 55.75: 055.75 – 58.54: 058.54 – 61.33: 461.33 – 64.11: 064.11 – 66.9: 4020406080
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
4.707 ± 10.6
Median
?50th percentile: half the non-missing values lie at or below it.
0.1
Range
?Smallest and largest recorded non-missing values.
0 – 66.9
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
2.24
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3 / 9.5
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

cec_usda_a723_cmolc_kg

target · numeric

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

cec_usda_a723_cmolc_kg distribution02004001 – 9.004: 3769.004 – 17.01: 28217.01 – 25.01: 20025.01 – 33.02: 14833.02 – 41.02: 8441.02 – 49.02: 2649.02 – 57.03: 657.03 – 65.03: 1265.03 – 73.04: 1273.04 – 81.04: 481.04 – 89.05: 289.05 – 97.05: 297.05 – 105.1: 4105.1 – 113.1: 2113.1 – 121.1: 4121.1 – 129.1: 2129.1 – 137.1: 0137.1 – 145.1: 2145.1 – 153.1: 2153.1 – 161.1: 4161.1 – 169.1: 0169.1 – 177.1: 2177.1 – 185.1: 0185.1 – 193.1: 2050100150200
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
20.53 ± 22.2
Median
?50th percentile: half the non-missing values lie at or below it.
14.6
Range
?Smallest and largest recorded non-missing values.
1 – 193.1
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.08
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.7 / 19
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

cf_usda_c236_w_pct

target · numeric

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

cf_usda_c236_w_pct distribution01002003000 – 2.708: 1022.708 – 5.417: 2165.417 – 8.125: 1568.125 – 10.83: 9010.83 – 13.54: 12213.54 – 16.25: 10016.25 – 18.96: 5218.96 – 21.67: 6021.67 – 24.38: 6824.38 – 27.08: 4827.08 – 29.79: 3229.79 – 32.5: 3432.5 – 35.21: 2435.21 – 37.92: 1437.92 – 40.62: 1640.62 – 43.33: 1043.33 – 46.04: 1446.04 – 48.75: 648.75 – 51.46: 251.46 – 54.17: 254.17 – 56.88: 056.88 – 59.58: 659.58 – 62.29: 062.29 – 65: 4020406080
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
14.34 ± 11.7
Median
?50th percentile: half the non-missing values lie at or below it.
12
Range
?Smallest and largest recorded non-missing values.
0 – 65
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.819
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
1.3 / 1.7
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

clay_tot_usda_a334_w_pct

target · numeric

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

clay_tot_usda_a334_w_pct distribution01002000 – 3.292: 1923.292 – 6.583: 866.583 – 9.875: 1109.875 – 13.17: 10213.17 – 16.46: 8216.46 – 19.75: 7819.75 – 23.04: 9023.04 – 26.33: 3626.33 – 29.62: 4229.62 – 32.92: 5432.92 – 36.21: 3836.21 – 39.5: 4039.5 – 42.79: 5242.79 – 46.08: 4046.08 – 49.38: 3049.38 – 52.67: 2052.67 – 55.96: 2255.96 – 59.25: 2859.25 – 62.54: 862.54 – 65.83: 1465.83 – 69.12: 669.12 – 72.42: 672.42 – 75.71: 075.71 – 79: 2020406080
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
21.54 ± 17.8
Median
?50th percentile: half the non-missing values lie at or below it.
17
Range
?Smallest and largest recorded non-missing values.
0 – 79
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.826
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.78 / -0.3
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

k_ext_usda_a725_cmolc_kg

target · numeric

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

k_ext_usda_a725_cmolc_kg distribution05001,0000 – 1.565: 8961.565 – 3.13: 2003.13 – 4.695: 484.695 – 6.259: 186.259 – 7.824: 67.824 – 9.389: 09.389 – 10.95: 210.95 – 12.52: 012.52 – 14.08: 014.08 – 15.65: 015.65 – 17.21: 217.21 – 18.78: 018.78 – 20.34: 020.34 – 21.91: 021.91 – 23.47: 023.47 – 25.04: 025.04 – 26.6: 026.6 – 28.17: 228.17 – 29.73: 029.73 – 31.3: 031.3 – 32.86: 032.86 – 34.43: 034.43 – 35.99: 235.99 – 37.56: 2010203040
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1.314 ± 2.67
Median
?50th percentile: half the non-missing values lie at or below it.
0.7284
Range
?Smallest and largest recorded non-missing values.
0 – 37.56
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
2.03
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
9.8 / 1.2e+02
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

n_tot_usda_a623_w_pct

target · numeric

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

n_tot_usda_a623_w_pct distribution02004006000 – 0.1392: 4580.1392 – 0.2783: 4500.2783 – 0.4175: 1140.4175 – 0.5567: 160.5567 – 0.6958: 180.6958 – 0.835: 160.835 – 0.9742: 140.9742 – 1.113: 181.113 – 1.252: 61.252 – 1.392: 101.392 – 1.531: 41.531 – 1.67: 21.67 – 1.809: 21.809 – 1.948: 61.948 – 2.087: 82.087 – 2.227: 42.227 – 2.366: 122.366 – 2.505: 62.505 – 2.644: 22.644 – 2.783: 22.783 – 2.922: 22.922 – 3.062: 43.062 – 3.201: 03.201 – 3.34: 401234
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
0.3236 ± 0.507
Median
?50th percentile: half the non-missing values lie at or below it.
0.16
Range
?Smallest and largest recorded non-missing values.
0 – 3.34
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.57
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.5 / 12
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

oc_usda_c729_w_pct

target · numeric

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

oc_usda_c729_w_pct distribution02505007500.1 – 2.322: 6882.322 – 4.543: 2704.543 – 6.765: 606.765 – 8.987: 208.987 – 11.21: 1811.21 – 13.43: 1413.43 – 15.65: 1015.65 – 17.87: 617.87 – 20.1: 620.1 – 22.32: 622.32 – 24.54: 424.54 – 26.76: 426.76 – 28.98: 228.98 – 31.2: 431.2 – 33.43: 633.43 – 35.65: 1035.65 – 37.87: 637.87 – 40.09: 1040.09 – 42.31: 642.31 – 44.53: 644.53 – 46.76: 646.76 – 48.98: 1048.98 – 51.2: 251.2 – 53.42: 40204060
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
5.231 ± 9.77
Median
?50th percentile: half the non-missing values lie at or below it.
1.96
Range
?Smallest and largest recorded non-missing values.
0.1 – 53.42
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.87
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
3.2 / 9.6
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

p_ext_usda_a274_mg_kg

target · numeric

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

p_ext_usda_a274_mg_kg distribution02004006000 – 12: 47612 – 24: 29224 – 36: 12236 – 48: 10248 – 60: 6460 – 72: 3672 – 84: 3084 – 96: 2296 – 108: 8108 – 120: 10120 – 132: 4132 – 144: 2144 – 156: 4156 – 168: 0168 – 180: 2180 – 192: 0192 – 204: 0204 – 216: 0216 – 228: 0228 – 240: 2240 – 252: 0252 – 264: 0264 – 276: 0276 – 288: 20100200300
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
23.8 ± 30.9
Median
?50th percentile: half the non-missing values lie at or below it.
15.4
Range
?Smallest and largest recorded non-missing values.
0 – 288
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
1.3
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
2.8 / 14
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

ph_cacl2_usda_a481_index

target · numeric

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

ph_cacl2_usda_a481_index distribution01002002.85 – 3.058: 163.058 – 3.266: 203.266 – 3.474: 283.474 – 3.682: 423.682 – 3.89: 463.89 – 4.098: 364.098 – 4.305: 604.305 – 4.513: 484.513 – 4.721: 404.721 – 4.929: 584.929 – 5.137: 445.137 – 5.345: 585.345 – 5.553: 385.553 – 5.761: 485.761 – 5.969: 685.969 – 6.177: 326.177 – 6.385: 326.385 – 6.593: 446.593 – 6.8: 346.8 – 7.008: 487.008 – 7.216: 1107.216 – 7.424: 1667.424 – 7.632: 587.632 – 7.84: 412510
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
5.694 ± 1.37
Median
?50th percentile: half the non-missing values lie at or below it.
5.77
Range
?Smallest and largest recorded non-missing values.
2.85 – 7.84
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.241
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.25 / -1.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

ph_h2o_usda_a268_index

target · numeric

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

ph_h2o_usda_a268_index distribution0501003.55 – 3.758: 63.758 – 3.967: 223.967 – 4.175: 404.175 – 4.383: 424.383 – 4.592: 464.592 – 4.8: 424.8 – 5.008: 405.008 – 5.217: 685.217 – 5.425: 405.425 – 5.633: 445.633 – 5.842: 665.842 – 6.05: 646.05 – 6.258: 586.258 – 6.467: 466.467 – 6.675: 466.675 – 6.883: 406.883 – 7.092: 467.092 – 7.3: 407.3 – 7.508: 807.508 – 7.717: 847.717 – 7.925: 947.925 – 8.133: 628.133 – 8.342: 508.342 – 8.55: 1212510
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
6.306 ± 1.31
Median
?50th percentile: half the non-missing values lie at or below it.
6.32
Range
?Smallest and largest recorded non-missing values.
3.55 – 8.55
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.208
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.19 / -1.2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

sand_tot_usda_c60_w_pct

target · numeric

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

sand_tot_usda_c60_w_pct distribution0501001500 – 4.083: 1404.083 – 8.167: 708.167 – 12.25: 9012.25 – 16.33: 5416.33 – 20.42: 5820.42 – 24.5: 5224.5 – 28.58: 4228.58 – 32.67: 4832.67 – 36.75: 5236.75 – 40.83: 5440.83 – 44.92: 4044.92 – 49: 4449 – 53.08: 4453.08 – 57.17: 4657.17 – 61.25: 3861.25 – 65.33: 5865.33 – 69.42: 4469.42 – 73.5: 3473.5 – 77.58: 3077.58 – 81.67: 3281.67 – 85.75: 2285.75 – 89.83: 3089.83 – 93.92: 2293.92 – 98: 340255075100
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
38.58 ± 28.5
Median
?50th percentile: half the non-missing values lie at or below it.
35
Range
?Smallest and largest recorded non-missing values.
0 – 98
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.738
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.35 / -1.1
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

silt_tot_usda_c62_w_pct

target · numeric

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

silt_tot_usda_c62_w_pct distribution0501001500 – 3.458: 1083.458 – 6.917: 326.917 – 10.38: 4410.38 – 13.83: 2413.83 – 17.29: 6217.29 – 20.75: 4820.75 – 24.21: 4624.21 – 27.67: 8027.67 – 31.12: 11631.12 – 34.58: 8034.58 – 38.04: 8438.04 – 41.5: 6641.5 – 44.96: 6644.96 – 48.42: 7248.42 – 51.88: 6051.88 – 55.33: 5255.33 – 58.79: 3458.79 – 62.25: 4862.25 – 65.71: 2065.71 – 69.17: 1669.17 – 72.62: 272.62 – 76.08: 676.08 – 79.54: 479.54 – 83: 80255075100
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
32.58 ± 18.7
Median
?50th percentile: half the non-missing values lie at or below it.
33
Range
?Smallest and largest recorded non-missing values.
0 – 83
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.574
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.02 / -0.58
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Metadata 12

ID_sample

metadata · categorical

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

ID_sample classes917158aeab35339a96567ca8882da…917158aeab35339a96567ca8882da8f2: 2252182fc0349091394114918ed24ad…52182fc0349091394114918ed24adf6b: 229c7c8a42a41f695012034083ec557…9c7c8a42a41f695012034083ec557e93: 22e7d83f5cd71e7bed32b617e03507e…e7d83f5cd71e7bed32b617e03507edf4: 223d9dbf0c7a7e8c6dab880d21086f6…3d9dbf0c7a7e8c6dab880d21086f6333: 2298ee07e432dc23532c010c823ef58…98ee07e432dc23532c010c823ef58222: 226b27a2e9c70e11829dda9d663caee…6b27a2e9c70e11829dda9d663caee1a8: 223ec7509a4f20e8686e4456c4f01e1…3ec7509a4f20e8686e4456c4f01e1894: 228126d85ee26e4ff17091d47e75571…8126d85ee26e4ff17091d47e75571357: 22ff45c67ca18c742be7d1be0e10210…ff45c67ca18c742be7d1be0e10210342: 22+10 more+10 more: 2020
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Classes
?Number of distinct recorded category values.
589
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.
917158aeab35339a96567ca8882da8f2 (2)

collection_name

metadata · categorical

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

collection_name classesossl_visnirossl_visnir: 589589ossl_mirossl_mir: 589589
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 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.
ossl_visnir (589)

spectral_kind

metadata · categorical

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

spectral_kind classesvisnirvisnir: 589589mirmir: 589589
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 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.
visnir (589)

scan_local_id

metadata · categorical

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

scan_local_id classes1107011070: 221107111071: 221107211072: 221107311073: 221107411074: 221107511075: 221107611076: 221107711077: 221107811078: 221107911079: 22+10 more+10 more: 2020
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Classes
?Number of distinct recorded category values.
589
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.
11070 (2)

scan_model_name

metadata · categorical

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

scan_model_name classesMetrohm NIRS XDS RapidContent…Metrohm NIRS XDS RapidContent Analyzer: 589589Bruker Vertex 70 with with Pi…Bruker Vertex 70 with with PikeAutoDiff accessory: 589589
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 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.
Metrohm NIRS XDS RapidContent Analyzer (589)

scan_model_code

metadata · categorical

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

scan_model_code classesMetrohm_NIRS_XDS_RapidContent…Metrohm_NIRS_XDS_RapidContent_Analyzer: 589589Bruker_Vertex_70.PikeAutoDiffBruker_Vertex_70.PikeAutoDiff: 589589
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 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.
Metrohm_NIRS_XDS_RapidContent_Analyzer (589)

feature_count_per_dimension

metadata · numeric

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

feature_count_per_dimension distribution02004006001,076 – 1102: 5891102 – 1128: 01128 – 1154: 01154 – 1180: 01180 – 1206: 01206 – 1232: 01232 – 1258: 01258 – 1284: 01284 – 1310: 01310 – 1336: 01336 – 1362: 01362 – 1388: 01388 – 1415: 01415 – 1441: 01441 – 1467: 01467 – 1493: 01493 – 1519: 01519 – 1545: 01545 – 1571: 01571 – 1597: 01597 – 1623: 01623 – 1649: 01649 – 1675: 01675 – 1,701: 5891,0002,0005,00010,000
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1388 ± 313
Median
?50th percentile: half the non-missing values lie at or below it.
1388
Range
?Smallest and largest recorded non-missing values.
1,076 – 1,701
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.225
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0 / -2
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

wavelength_note

metadata · categorical

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

wavelength_note classesossl_visnir_350_2500_nm_step_2ossl_visnir_350_2500_nm_step_2: 589589ossl_mir_600_4000_cm_minus_1_…ossl_mir_600_4000_cm_minus_1_step_2: 589589
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 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.
ossl_visnir_350_2500_nm_step_2 (589)

replaces_dataset_id

metadata · categorical

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

replaces_dataset_id classesossl_regression_e9e5102cossl_regression_e9e5102c: 589589ossl_regression_83467e4eossl_regression_83467e4e: 589589
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 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.
ossl_regression_e9e5102c (589)

site_id

metadata · identifier

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

site_id classes4326240243262402: 224488271444882714: 224746263647462636: 224778268647782686: 224650215846502158: 224612207446122074: 224724263847242638: 224692161246921612: 225100418851004188: 225302450653024506: 22+10 more+10 more: 2020
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Classes
?Number of distinct recorded category values.
589
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.
43262402 (2)

longitude

metadata · numeric

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

longitude distribution0100200-9.153 – -7.481: 110-7.481 – -5.809: 50-5.809 – -4.137: 0-4.137 – -2.465: 0-2.465 – -0.7935: 0-0.7935 – 0.8784: 00.8784 – 2.55: 02.55 – 4.222: 104.222 – 5.894: 305.894 – 7.566: 207.566 – 9.238: 469.238 – 10.91: 3010.91 – 12.58: 8812.58 – 14.25: 12814.25 – 15.93: 15815.93 – 17.6: 8217.6 – 19.27: 5419.27 – 20.94: 4220.94 – 22.61: 6622.61 – 24.28: 9824.28 – 25.96: 5025.96 – 27.63: 5427.63 – 29.3: 4629.3 – 30.97: 16-2002040
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
13.85 ± 10.4
Median
?50th percentile: half the non-missing values lie at or below it.
14.99
Range
?Smallest and largest recorded non-missing values.
-9.153 – 30.97
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.753
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.86 / 0.071
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

latitude

metadata · numeric

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

latitude distribution05010015036.8 – 38.15: 12438.15 – 39.5: 5439.5 – 40.85: 7840.85 – 42.2: 10242.2 – 43.56: 6243.56 – 44.91: 3844.91 – 46.26: 4246.26 – 47.61: 6047.61 – 48.97: 3048.97 – 50.32: 6250.32 – 51.67: 8451.67 – 53.02: 9053.02 – 54.37: 4254.37 – 55.73: 2455.73 – 57.08: 2857.08 – 58.43: 1058.43 – 59.78: 1859.78 – 61.14: 5461.14 – 62.49: 6062.49 – 63.84: 5063.84 – 65.19: 4465.19 – 66.54: 866.54 – 67.9: 867.9 – 69.25: 6102050100
n / missing
?Recorded observation count and number of missing values for this variable.
1,178 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
49.22 ± 8.72
Median
?50th percentile: half the non-missing values lie at or below it.
48.91
Range
?Smallest and largest recorded non-missing values.
36.8 – 69.25
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.177
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.36 / -1
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no
Constant metadata 14

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

  • SpectralRep1
  • datasetOSSL snapshot v1.2
  • dataset_codeLUCAS.WOODWELL.SSL
  • dataset_ownerEuropean Soil Data Centre (ESDAC), European Commission, Joint Research Centre
  • scan_opticsKBr beamsplitter, Gold mirror, Mirror background
  • scan_preparationSieved <2 mm
  • upper_depth_cm0
  • lower_depth_cm20
  • dimensions1D
  • active_statusactive
  • campaign_date_begin2009-05-01
  • campaign_date_end2012-08-01
  • location_error_m1,000
  • campaign_year2,009

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
Samples589
Observations (total)1,178
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

originalall: 589 documented · not applied

Load this dataset

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

# Download original raw resources; no Dataverse token required
from nirs4all_datasets import retrieve
result = retrieve("ossl_lucas_woodwell_soil_all_y", prepare=False)
print(result["resources"])
# Raw resources may need dataset-specific assembly before analysis

Metadata downloads are available for public datasets only. The dataset bytes are never served here — fetch them from the origin / DOI above.

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