← Back to the catalog
Restricted redistributiontoken access / hosting pending2 sources

GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i

github · NIR

GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i. Origin database composed from 2 standardized v2.0 leaves: 2 spectral source(s), 4 declared target(s). Auto-generated from dataset_card.json (verify before publication).

nirv2github
🔒
No automatic open retrieval route is recorded. Full metadata and metrics are shown. Check the origin links for manual access. A hosted canonical download needs a configured Dataverse DOI and token; a token alone cannot make an unhosted dataset available.
556
samples
—
wavelengths
2
sources
4
targets
20
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

ContributorHyperspectral sensing for high-throughput chloride detection in grapevines
Conversion statuspartial

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.
RedistributionWiley article is Open Access and points to GitHub data, but the GitHub repository API reports no explicit repository license.
Content version1.1.0
Schema / protocol2.0
Content hashcbfee889281bf3c6…
Processing hash083037fda0c03942…
Metadata hasha3cbbf2b51dc0d7d…

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 score0.56
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.

GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i property profile0.250.50.751integritynoiseartefactsbaselinePCA outliersreferencerepeatabilitystructureGitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i — integrity: 0.00GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i — noise: 0.01GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i — artefacts: 1.00GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i — baseline: 0.84GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i — PCA outliers: 0.66GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i — reference: 0.47GitHub grapevine leaf chloride, NIR-S-G1 and SVC HR-1024i — structure: 0.92GitHub grapevin…0 center · 1 outer ring · outward = stronger anomaly / heterogeneity signal

Profile axes

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

Integrity
?Combines missing cells, zero columns and infinite values. Higher values call for checking data completeness.
0.00
Noise
?Combines roughness and its signal-to-roughness proxy. Real narrow bands may also contribute.
0.01
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.
0.84
PCA outliers
?Combines relative PCA residual and score-distance tails. Valid rare spectra can produce a high value.
0.66
Distance to average spectrum
?Dispersion around this dataset's mean spectrum, using distance, shape and shift summaries.
0.47
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.
0.92

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 scoreOffset compatible with a different white referenceOffset compatible with a different white reference: 0.700.70Signature compatible with a spectral spliceSignature compatible with a spectral splice: 0.680.68Signature compatible with a different backgroundSignature compatible with a different background: 0.650.65Signature compatible with a population shiftSignature compatible with a population shift: 0.590.59Signature compatible with clippingSignature compatible with clipping: 0.420.42High spectral roughness signatureHigh spectral roughness signature: 0.260.26Flat spectrum/weak signalFlat spectrum/weak signal: 0.100.10

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
Offset compatible with a different white referenceX_nirs_g10.70medium100 %Baseline/mean/area 1.00, local artifacts 1.00, Mahalanobis / T2 0.84Systematic 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 spectral spliceX_svc_hr1024i0.68medium100 %Spike rate 1.00, Jump rate 1.00, Undegraded roughness S/N proxy 1.00Break at detector junctions, local calibration or different probe.Check the white/black reference actually acquired and its metadata.
Check instrument, probe, geometry, campaign and processing/resampling log.
Check the repeat protocol before interpreting an intra-ID dispersion.
Signature compatible with a different backgroundX_nirs_g10.65medium100 %Baseline/mean/area 1.00, Mahalanobis / T2 0.84, RMS/SAM to mean spectrum 0.54Systematic 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_nirs_g10.59medium100 %PCA structure 1.00, Mahalanobis / T2 0.84, RMS/SAM to mean spectrum 0.54Different 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_nirs_g10.42medium100 %Baseline/mean/area 1.00, Jump rate 1.00, PCA Q 0.51Detector 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_svc_hr1024i0.26weak100 %Spike rate 1.00, RMS/SAM to mean spectrum 0.40, PCA Q 0.29Weak 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_nirs_g10.10weak100 %PCA Q 0.51Bad 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_nirs_g1—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
X_nirs_g1259259
X_svc_hr1024i556556

259 sample units are measured by every source; 297 by a single source. Sources are joined by declared sample identity, never by row position.

X_nirs_g1

X_nirs_g1 · NIR · NIR-S-G1

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

Spectral signal summary

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

X_nirs_g1 spectra0.00.20.40.60.87501,0001,2501,5001,750q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm901nm — median 0.5817 (q25–q75 0.5545–0.6038)909nm — median 0.5819 (q25–q75 0.5557–0.6053)913nm — median 0.5812 (q25–q75 0.5545–0.6036)922nm — median 0.576 (q25–q75 0.5522–0.6005)930nm — median 0.5744 (q25–q75 0.5505–0.598)934nm — median 0.5741 (q25–q75 0.5498–0.599)941nm — median 0.576 (q25–q75 0.551–0.6)945nm — median 0.5761 (q25–q75 0.5508–0.5988)953nm — median 0.5749 (q25–q75 0.5484–0.5971)962nm — median 0.5735 (q25–q75 0.547–0.5944)966nm — median 0.572 (q25–q75 0.5461–0.5934)973nm — median 0.573 (q25–q75 0.5467–0.5935)981nm — median 0.573 (q25–q75 0.548–0.5949)985nm — median 0.5748 (q25–q75 0.5485–0.5948)993nm — median 0.5759 (q25–q75 0.5505–0.5973)996nm — median 0.5774 (q25–q75 0.551–0.5981)1,005nm — median 0.5797 (q25–q75 0.553–0.6012)1,013nm — median 0.5811 (q25–q75 0.554–0.6024)1,017nm — median 0.5825 (q25–q75 0.5554–0.6041)1,024nm — median 0.5853 (q25–q75 0.5575–0.6062)1,032nm — median 0.5864 (q25–q75 0.5587–0.6076)1,036nm — median 0.5872 (q25–q75 0.5599–0.6087)1,043nm — median 0.5882 (q25–q75 0.5612–0.6099)1,052nm — median 0.5892 (q25–q75 0.5619–0.6101)1,056nm — median 0.5894 (q25–q75 0.5625–0.611)1,063nm — median 0.5897 (q25–q75 0.5628–0.6108)1,067nm — median 0.5897 (q25–q75 0.5636–0.6118)1,074nm — median 0.5907 (q25–q75 0.5641–0.6119)1,082nm — median 0.5899 (q25–q75 0.5636–0.6116)1,085nm — median 0.5897 (q25–q75 0.5636–0.6117)1,094nm — median 0.5887 (q25–q75 0.5628–0.611)1,101nm — median 0.5888 (q25–q75 0.5621–0.6096)1,105nm — median 0.588 (q25–q75 0.5616–0.609)1,112nm — median 0.587 (q25–q75 0.5604–0.6082)1,120nm — median 0.585 (q25–q75 0.5591–0.606)1,123nm — median 0.5845 (q25–q75 0.5575–0.6054)1,132nm — median 0.5785 (q25–q75 0.5535–0.6001)1,136nm — median 0.5754 (q25–q75 0.5498–0.5961)1,143nm — median 0.5662 (q25–q75 0.5421–0.588)1,150nm — median 0.5574 (q25–q75 0.5339–0.5796)1,154nm — median 0.554 (q25–q75 0.5312–0.576)1,161nm — median 0.5518 (q25–q75 0.5286–0.5749)1,170nm — median 0.5514 (q25–q75 0.528–0.5727)1,173nm — median 0.5517 (q25–q75 0.5276–0.5733)1,180nm — median 0.5518 (q25–q75 0.5281–0.5731)1,184nm — median 0.5524 (q25–q75 0.5285–0.573)1,191nm — median 0.5519 (q25–q75 0.5282–0.5736)1,198nm — median 0.5537 (q25–q75 0.5301–0.5754)1,202nm — median 0.5542 (q25–q75 0.5305–0.5757)1,210nm — median 0.5562 (q25–q75 0.5329–0.5776)1,217nm — median 0.5578 (q25–q75 0.5347–0.5798)1,221nm — median 0.5589 (q25–q75 0.5356–0.5811)1,228nm — median 0.5602 (q25–q75 0.5368–0.583)1,235nm — median 0.5616 (q25–q75 0.5381–0.5838)1,239nm — median 0.5616 (q25–q75 0.5385–0.5841)1,247nm — median 0.5629 (q25–q75 0.5394–0.5852)1,250nm — median 0.5634 (q25–q75 0.5395–0.5857)1,257nm — median 0.5635 (q25–q75 0.5403–0.5859)1,264nm — median 0.5641 (q25–q75 0.541–0.5867)1,268nm — median 0.5647 (q25–q75 0.5411–0.5868)1,275nm — median 0.5637 (q25–q75 0.54–0.5863)1,282nm — median 0.5616 (q25–q75 0.5387–0.585)1,286nm — median 0.5607 (q25–q75 0.5375–0.5838)1,293nm — median 0.5583 (q25–q75 0.5351–0.5816)1,300nm — median 0.5552 (q25–q75 0.5324–0.5784)1,304nm — median 0.5529 (q25–q75 0.5301–0.576)1,311nm — median 0.548 (q25–q75 0.5253–0.5703)1,314nm — median 0.545 (q25–q75 0.5225–0.5676)1,321nm — median 0.5382 (q25–q75 0.5154–0.5602)1,329nm — median 0.5289 (q25–q75 0.5065–0.5506)1,332nm — median 0.5244 (q25–q75 0.5026–0.5459)1,339nm — median 0.5164 (q25–q75 0.4938–0.5364)1,346nm — median 0.5091 (q25–q75 0.4852–0.5283)1,349nm — median 0.5049 (q25–q75 0.4809–0.5246)1,356nm — median 0.4975 (q25–q75 0.4749–0.5175)1,359nm — median 0.4929 (q25–q75 0.471–0.514)1,367nm — median 0.4819 (q25–q75 0.4606–0.5021)1,374nm — median 0.464 (q25–q75 0.4429–0.484)1,377nm — median 0.4498 (q25–q75 0.4318–0.4706)1,384nm — median 0.4146 (q25–q75 0.3959–0.4364)1,391nm — median 0.3659 (q25–q75 0.3472–0.3894)1,394nm — median 0.3412 (q25–q75 0.3233–0.3638)1,402nm — median 0.289 (q25–q75 0.2695–0.311)1,409nm — median 0.2573 (q25–q75 0.2373–0.2786)1,412nm — median 0.2453 (q25–q75 0.2258–0.2666)1,419nm — median 0.2307 (q25–q75 0.2112–0.2515)1,422nm — median 0.2268 (q25–q75 0.2073–0.2464)1,428nm — median 0.221 (q25–q75 0.2023–0.2416)1,436nm — median 0.2189 (q25–q75 0.1998–0.2398)1,439nm — median 0.2199 (q25–q75 0.1995–0.2398)1,446nm — median 0.2206 (q25–q75 0.2006–0.2416)1,452nm — median 0.2228 (q25–q75 0.2033–0.2443)1,456nm — median 0.2243 (q25–q75 0.2048–0.2458)1,462nm — median 0.2298 (q25–q75 0.2093–0.2507)1,469nm — median 0.237 (q25–q75 0.2168–0.2588)1,473nm — median 0.2438 (q25–q75 0.2241–0.2657)1,479nm — median 0.2566 (q25–q75 0.2355–0.2775)1,483nm — median 0.2626 (q25–q75 0.2414–0.2839)1,489nm — median 0.2754 (q25–q75 0.2538–0.297)1,496nm — median 0.2874 (q25–q75 0.2659–0.31)1,499nm — median 0.2937 (q25–q75 0.2723–0.3158)1,505nm — median 0.3059 (q25–q75 0.2845–0.3291)1,513nm — median 0.3193 (q25–q75 0.2983–0.3434)1,516nm — median 0.3254 (q25–q75 0.3048–0.349)1,522nm — median 0.3381 (q25–q75 0.3164–0.3623)1,525nm — median 0.3434 (q25–q75 0.3219–0.3676)1,532nm — median 0.355 (q25–q75 0.3332–0.3785)1,538nm — median 0.3654 (q25–q75 0.3442–0.3884)1,542nm — median 0.3724 (q25–q75 0.3507–0.3939)1,548nm — median 0.3817 (q25–q75 0.3597–0.4029)1,555nm — median 0.3899 (q25–q75 0.3685–0.4114)1,558nm — median 0.3939 (q25–q75 0.3725–0.4158)1,564nm — median 0.4015 (q25–q75 0.3797–0.4237)1,570nm — median 0.4091 (q25–q75 0.3876–0.4307)1,573nm — median 0.4126 (q25–q75 0.391–0.4344)1,581nm — median 0.4197 (q25–q75 0.3985–0.4419)1,584nm — median 0.4228 (q25–q75 0.401–0.4448)1,590nm — median 0.4271 (q25–q75 0.4064–0.4497)1,596nm — median 0.4314 (q25–q75 0.411–0.4532)1,599nm — median 0.4325 (q25–q75 0.4124–0.4548)1,605nm — median 0.4344 (q25–q75 0.4142–0.4569)1,612nm — median 0.4371 (q25–q75 0.4164–0.4581)1,615nm — median 0.4377 (q25–q75 0.4169–0.4585)1,621nm — median 0.4392 (q25–q75 0.419–0.4609)1,627nm — median 0.4413 (q25–q75 0.4207–0.4621)1,630nm — median 0.4414 (q25–q75 0.4206–0.4628)1,636nm — median 0.4429 (q25–q75 0.4224–0.4644)1,639nm — median 0.4435 (q25–q75 0.4228–0.4656)1,646nm — median 0.443 (q25–q75 0.4234–0.4642)1,652nm — median 0.4443 (q25–q75 0.4238–0.4666)1,655nm — median 0.445 (q25–q75 0.424–0.4672)1,661nm — median 0.4439 (q25–q75 0.4242–0.4682)1,667nm — median 0.4483 (q25–q75 0.4257–0.4718)1,670nm — median 0.4521 (q25–q75 0.43–0.4771)1,677nm — median 0.4669 (q25–q75 0.4332–0.5026)1,680nm — median 0.4675 (q25–q75 0.4354–0.5181)1,686nm — median 0.4757 (q25–q75 0.4394–0.5436)1,692nm — median 0.478 (q25–q75 0.4436–0.5558)1,695nm — median 0.4795 (q25–q75 0.4436–0.5609)1,702nm — median 0.4739 (q25–q75 0.4385–0.5418)

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.
228
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
901–1,702 nm
Mean spacing
?Average difference between adjacent spectral-axis coordinates; compare only within the same unit.
3.53 nm
Grid
?Uniform means adjacent axis spacings are approximately equal. An irregular grid may need care when applying derivatives.
irregular
Observations
?Exported spectral rows in this source, including repeated measurements when present.
259

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.
0.155 – 0.949
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
0.221 – 0.6
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
0.4812
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
390.6
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
0.3791
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
0.00068302
Roughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR.
7e+02
Roughness S/N proxy dB
?20 log10 of the roughness signal-to-noise proxy. Units are decibels; compare only compatible signal representations.
6e+01 dB
Dynamic range
?Maximum minus minimum of the mean spectrum. Its magnitude depends on the signal representation.
0.379
Smoothness
?Mean per-spectrum RMS of second differences, in signal units. Smaller values indicate smoother spectra under this protocol.
0.002522
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.
72

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.
205
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
0.35%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
1,233
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
2.10%
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.
-0.27564
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.0024704
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.005848
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
0.029733
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
0.064958
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.031211
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.065872
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
0.12655
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
0.28033
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
0.020648
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
Hotelling T2 p95/median
?Hotelling T² measures distance within the retained PCA subspace, scaled by component variance. Ratio of the 95th percentile to the median.
6.8
Mahalanobis H p95/median
?Distance from the PCA-score center after variance scaling. Ratio of the 95th percentile to the median; large values identify relatively extreme spectra.
2.6
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.
3
Top-10 cum. var
?Fraction of spectral variance explained by up to the first ten computed principal components, displayed as a percentage.
100.0%
Computed metric scores 30highest alert 1.00

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

FamilyComputed metricValueAlert scoreHeuristic levelDescriptive interpretationPossible causes to verifyCalculation / scoring
Data integrityInvalid/masked cell count (owner report)
?Count of cells reported unavailable by the native owner under its null or validity mask. This count is distinct from the historical NaN ratio; consult the recorded population and denominator. Scoring: No alert mapping is defined for this metric; an unavailable score does not mean a zero measured value. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.missing_cells		——not calculableNot enough information to score this metric on this dataset.Missing data or validity mask; not evidence of an acquisition causeNative Preflight count of cells unavailable under x/null and valid_mask; denominator stays in native_metric.denominators.n_cells. Not legacy NaN ratio.
Data integrityNaN ratio
?Missing spectral cells divided by all spectral cells, displayed as a percentage. Scoring: alert = min(1, nan_ratio / 0.05). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.nan_ratio		0%0.00weakFull spectrumAcquisition/export errorcount(isnan(X)) / X.sizealert = min(1, nan_ratio / 0.05)
Data integrityInf count
?Number of positive or negative infinite spectral values; investigate invalid calculations or export. Scoring: alert = min(1, inf_count / 1). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.inf_count		00.00weakNormalInvalid calculationscount(isinf(X))alert = min(1, inf_count / 1)
Data integrityZero ratio
?Exactly zero spectral cells divided by all cells. Zero can be a valid measurement and is not automatically missing. Scoring: alert = min(1, zero_ratio / 0.05). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
integrity.zero_ratio		0%0.00weakNormalExport, saturationcount(X == 0) / count(finite X)alert = min(1, zero_ratio / 0.05)
Overall amplitudeMean reflectance
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations. Scoring: alert reuses baseline/shape drift because absolute reflectance ranges are technology-dependent. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
amplitude.mean_reflectance		0.48121.00strongAtypical 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		390.631.00strongAtypical 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		0.379130.00weakStrong 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		0.0173280.00weakNormal 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		0.000683020.03weakStableLamp, 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		704.520.00weakGood 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		104.280.00weakReliable 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		2050.35weakClean spectrumCosmic 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		0.35%0.35weakNormalInterpolationspike_count / (n_samples * (n_features - 2))alert = min(1, spike_rate / 0.01)
Local artifactsJump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins. Scoring: alert follows jump_rate, saturated at 1%. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
artefacts.jump_count		1,2331.00strongDetector 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		2.1%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		0.00339%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		-0.275641.00strongDriftIlluminationlinear 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		0.00247040.51mediumUnusual shapeBackground, 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		0.0058480.24weakFlatBiology 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		4.04610.51mediumAtypical spectrumArtifact, mixturep95(Q/SPE residual) / median(Q/SPE residual)alert = min(1, pca_q_ratio / 8)
Multivariate outliersHotelling T²
?Hotelling T² measures distance within the retained PCA subspace, scaled by component variance. Ratio of the 95th percentile to the median. Scoring: alert = min(1, hotelling_t2_ratio / 8). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.hotelling_t2_ratio		6.75810.84strongExtreme but consistentNatural variabilityp95(Hotelling T2) / median(Hotelling T2)alert = min(1, hotelling_t2_ratio / 8)
Multivariate outliersMahalanobis H
?Distance from the PCA-score center after variance scaling. Ratio of the 95th percentile to the median; large values identify relatively extreme spectra. Scoring: alert = min(1, mahalanobis_h_ratio / 4). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
outliers.mahalanobis_h_ratio		2.59960.65mediumGlobal 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		0.0649580.54mediumDifferent 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		0.0658720.19weakSimilarBackground, 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		13.4281.00strongSubpopulationsDifferent batches1 / median kNN distance in PCA score spacealert follows density_cv/profile structure complexity, not raw density alone
Structure of the datasetkNN distance ratio (not LOF)
?95th percentile of mean k-nearest-neighbor distance divided by the population median of that distance, in PCA-score space. Values above 1 indicate an upper tail with more isolated observations; valid rare spectra can also be isolated. This distance ratio is not the Local Outlier Factor algorithm. Scoring: alert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2). Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.knn_distance_ratio_p95		3.68791.00strongIsolated spectrumRare casesp95(mean kNN distance / median population mean kNN distance) in PCA-score space; not LOFalert = min(1, max(0, kNN_distance_ratio_p95 - 1) / 2)
Structure of the datasetIsolation Forest score
?95th percentile of the negated Isolation Forest score in retained PCA-score space. Larger raw scores indicate easier isolation under that model; the scale is implementation-dependent. The displayed alert reuses structure complexity rather than directly mapping this raw score. Scoring: alert follows structure complexity; raw score is implementation-dependent. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
structure.isolation_forest_score_p95		0.60761.00strongAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source X_nirs_g1: 259 of 259 source observations are plotted. PC1 captures 89.1% and PC2 7.6% 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.

X_nirs_g1 PCA score plot-2024-1.0-0.50.00.51.0PC1 0.01295 · PC2 -0.0984PC1 -0.1957 · PC2 -0.1069PC1 -0.1773 · PC2 -0.45PC1 -0.7454 · PC2 0.04309PC1 -0.4625 · PC2 0.2524PC1 -0.423 · PC2 -0.3052PC1 -0.3086 · PC2 0.1735PC1 -0.002852 · PC2 0.06595PC1 -0.3248 · PC2 0.168PC1 0.5663 · PC2 -0.05954PC1 -0.4887 · PC2 0.02563PC1 -0.447 · PC2 -0.002231PC1 0.5431 · PC2 -0.6029PC1 -0.06895 · PC2 -0.001635PC1 0.2417 · PC2 -0.2764PC1 -0.04522 · PC2 0.3064PC1 -0.09518 · PC2 -0.2329PC1 -0.02189 · PC2 0.07791PC1 -0.6483 · PC2 0.1762PC1 0.2738 · PC2 0.3146PC1 -0.7974 · PC2 0.04834PC1 -0.126 · PC2 -0.1971PC1 -1.108 · PC2 -0.3694PC1 -0.4993 · PC2 0.1643PC1 -0.3629 · PC2 -0.03132PC1 0.2326 · PC2 -0.07296PC1 0.4183 · PC2 0.03373PC1 -0.46 · PC2 0.1489PC1 0.2584 · PC2 -0.02458PC1 0.7678 · PC2 -0.117PC1 -0.09224 · PC2 0.1696PC1 -0.4717 · PC2 0.1471PC1 0.483 · PC2 -0.2048PC1 -0.353 · PC2 0.3031PC1 -0.06719 · PC2 -0.1207PC1 -0.1705 · PC2 0.2712PC1 -0.1673 · PC2 0.372PC1 -0.01797 · PC2 0.1795PC1 -0.05572 · PC2 0.2229PC1 -0.4396 · PC2 -0.1506PC1 -0.2737 · PC2 -0.4135PC1 -0.1655 · PC2 -0.1413PC1 0.6006 · PC2 -0.05964PC1 -0.3561 · PC2 0.2524PC1 0.6195 · PC2 -0.007944PC1 -0.3748 · PC2 -0.2498PC1 0.5945 · PC2 -0.06053PC1 -0.547 · PC2 -0.0372PC1 0.006741 · PC2 0.1015PC1 -0.2324 · PC2 -0.3033PC1 0.3065 · PC2 -0.4401PC1 -0.1112 · PC2 0.08927PC1 0.1033 · PC2 -0.05808PC1 0.8322 · PC2 -0.06121PC1 0.475 · PC2 -0.3112PC1 -0.6996 · PC2 -0.05314PC1 -0.708 · PC2 0.1507PC1 0.5255 · PC2 0.0263PC1 -0.6626 · PC2 0.02613PC1 -0.03626 · PC2 -0.05743PC1 -0.4205 · PC2 0.2151PC1 0.1236 · PC2 -0.3569PC1 -0.3366 · PC2 -0.1717PC1 -0.099 · PC2 -0.1255PC1 -0.03398 · PC2 -0.3007PC1 -0.4385 · PC2 0.04392PC1 0.0723 · PC2 0.1852PC1 -1.084 · PC2 0.3081PC1 0.06712 · PC2 -0.1816PC1 0.04096 · PC2 -0.1892PC1 0.1508 · PC2 -0.4507PC1 0.2948 · PC2 0.0587PC1 -0.3709 · PC2 0.08377PC1 0.621 · PC2 -0.0285PC1 0.282 · PC2 -0.3188PC1 -0.4685 · PC2 0.3191PC1 -0.4029 · PC2 0.00102PC1 -0.2587 · PC2 -0.04367PC1 -0.4511 · PC2 -0.126PC1 -0.5691 · PC2 0.2469PC1 0.1702 · PC2 -0.2551PC1 3.693 · PC2 0.03474PC1 -0.1024 · PC2 -0.1158PC1 -0.1453 · PC2 -0.2554PC1 0.5019 · PC2 -0.04692PC1 -0.5859 · PC2 0.1038PC1 -0.2446 · PC2 -0.3725PC1 -0.3649 · PC2 -0.2019PC1 -0.1472 · PC2 -0.2714PC1 -0.6582 · PC2 -0.02901PC1 -0.1959 · PC2 -0.3763PC1 0.1348 · PC2 -0.07913PC1 0.2748 · PC2 0.02247PC1 0.2008 · PC2 -0.129PC1 -0.5725 · PC2 -0.03234PC1 -0.5149 · PC2 0.021PC1 -0.1727 · PC2 0.1872PC1 0.7456 · PC2 -0.1753PC1 -0.4258 · PC2 -0.1228PC1 -0.426 · PC2 0.09772PC1 -0.4524 · PC2 0.3348PC1 -0.5648 · PC2 0.3176PC1 0.3428 · PC2 0.142PC1 -0.6857 · PC2 0.1018PC1 -0.4189 · PC2 0.195PC1 0.1925 · PC2 0.08926PC1 0.2693 · PC2 -0.1475PC1 -0.3316 · PC2 0.2999PC1 -0.08584 · PC2 -0.1844PC1 -0.4962 · PC2 0.1784PC1 -0.486 · PC2 0.3657PC1 0.01721 · PC2 0.1625PC1 -0.0349 · PC2 0.4096PC1 -0.666 · PC2 0.01032PC1 -0.3794 · PC2 -0.1946PC1 -0.5851 · PC2 0.144PC1 -0.3352 · PC2 -0.01178PC1 -0.1116 · PC2 0.2379PC1 -0.06541 · PC2 0.1049PC1 -0.4169 · PC2 -0.2846PC1 -0.4412 · PC2 0.228PC1 -0.4248 · PC2 0.2293PC1 -0.4105 · PC2 -0.003101PC1 -0.6281 · PC2 -0.3214PC1 -0.5449 · PC2 -0.3127PC1 -1.183 · PC2 0.1613PC1 -0.1324 · PC2 -0.2855PC1 -0.4047 · PC2 -0.1055PC1 0.1276 · PC2 0.3326PC1 0.01101 · PC2 -0.2442PC1 -0.4058 · PC2 0.3604PC1 0.4397 · PC2 -0.2614PC1 0.126 · PC2 0.1558PC1 0.03632 · PC2 -0.5578PC1 -0.4717 · PC2 0.001938PC1 -0.8068 · PC2 0.357PC1 0.1141 · PC2 -0.1932PC1 -0.5988 · PC2 0.269PC1 -0.9578 · PC2 -0.05434PC1 -0.409 · PC2 -0.1227PC1 -0.5808 · PC2 0.2261PC1 0.3226 · PC2 -0.0558PC1 -0.5932 · PC2 -0.02575PC1 -0.5225 · PC2 0.534PC1 -0.3821 · PC2 0.09161PC1 -0.06341 · PC2 0.1473PC1 0.0573 · PC2 0.1133PC1 -0.5122 · PC2 0.3476PC1 -0.3087 · PC2 0.1367PC1 -0.4479 · PC2 0.227PC1 0.4913 · PC2 -0.06403PC1 -0.3875 · PC2 0.0361PC1 -0.2296 · PC2 0.2664PC1 -0.836 · PC2 0.3424PC1 -0.1147 · PC2 -0.3047PC1 0.0861 · PC2 -0.06236PC1 -0.2595 · PC2 0.1537PC1 -0.01972 · PC2 0.1015PC1 -0.4711 · PC2 0.1237PC1 0.3337 · PC2 0.01807PC1 -0.2043 · PC2 0.2445PC1 0.4586 · PC2 -0.05375PC1 0.415 · PC2 0.1122PC1 -0.5266 · PC2 0.09672PC1 -0.8975 · PC2 0.3186PC1 0.1335 · PC2 0.119PC1 0.04291 · PC2 -0.1024PC1 0.1476 · PC2 -0.02972PC1 0.1707 · PC2 -0.16PC1 -0.04813 · PC2 0.2179PC1 -0.04481 · PC2 0.2088PC1 0.0307 · PC2 -0.1546PC1 -0.06976 · PC2 0.1706PC1 -0.2928 · PC2 -0.2861PC1 -0.3465 · PC2 -0.1942PC1 -0.0009218 · PC2 0.03281PC1 -0.03474 · PC2 0.233PC1 0.05616 · PC2 0.2867PC1 -0.5133 · PC2 -0.04329PC1 -0.4205 · PC2 -0.1794PC1 -0.05931 · PC2 0.06718PC1 -0.2577 · PC2 -0.4829PC1 -0.3476 · PC2 -0.3013PC1 -0.7609 · PC2 -0.05987PC1 -0.1737 · PC2 0.1725PC1 -0.4 · PC2 -0.1262PC1 0.02959 · PC2 -0.121PC1 0.3128 · PC2 0.01154PC1 0.4354 · PC2 -0.03694PC1 0.5423 · PC2 -0.03128PC1 0.0625 · PC2 -0.03792PC1 -0.2859 · PC2 -0.2305PC1 -0.4606 · PC2 0.1824PC1 -0.1161 · PC2 0.051PC1 -0.6214 · PC2 -0.1586PC1 0.1226 · PC2 0.04291PC1 -0.1814 · PC2 -0.4172PC1 0.976 · PC2 -0.6898PC1 -0.3848 · PC2 -0.08988PC1 -0.07557 · PC2 -0.08257PC1 -0.5067 · PC2 -0.3008PC1 -0.2213 · PC2 0.3916PC1 0.07397 · PC2 0.484PC1 -0.1602 · PC2 -0.1845PC1 -0.07296 · PC2 0.2473PC1 0.00563 · PC2 -0.08917PC1 0.2815 · PC2 -0.2831PC1 0.6572 · PC2 -0.2698PC1 -0.2831 · PC2 -0.01608PC1 0.6625 · PC2 -0.2883PC1 -0.3204 · PC2 0.3816PC1 -0.3226 · PC2 -0.003934PC1 0.5055 · PC2 -0.2188PC1 -0.1232 · PC2 0.2435PC1 -0.01241 · PC2 0.2331PC1 -0.09702 · PC2 -0.3321PC1 -0.3908 · PC2 0.1362PC1 0.3099 · PC2 -0.1344PC1 -0.7746 · PC2 0.3858PC1 0.5956 · PC2 -0.143PC1 0.2961 · PC2 -0.5083PC1 0.4286 · PC2 -0.07115PC1 0.4279 · PC2 -0.3499PC1 3.664 · PC2 0.172PC1 3.35 · PC2 0.6876PC1 3.794 · PC2 0.1049PC1 -0.3431 · PC2 -0.07382PC1 0.3733 · PC2 0.09859PC1 0.1382 · PC2 0.1271PC1 -0.1966 · PC2 0.1124PC1 -0.1785 · PC2 -0.2715PC1 0.02371 · PC2 -0.2809PC1 0.3498 · PC2 -0.2099PC1 -0.1179 · PC2 0.2466PC1 3.474 · PC2 0.2733PC1 3.493 · PC2 -0.1492PC1 3.762 · PC2 0.3301PC1 0.0004132 · PC2 0.1814PC1 3.635 · PC2 0.1995PC1 0.3321 · PC2 -0.07444PC1 -0.5548 · PC2 0.009129PC1 0.1819 · PC2 -0.06804PC1 -0.03511 · PC2 0.06442PC1 3.146 · PC2 0.2696PC1 -0.7487 · PC2 0.1978PC1 -0.3568 · PC2 0.5325PC1 0.4746 · PC2 -0.2324PC1 0.6698 · PC2 -0.1891PC1 0.1459 · PC2 -0.01244PC1 -0.09321 · PC2 -0.1318PC1 -0.03175 · PC2 -0.129PC1 0.09699 · PC2 0.02414PC1 -0.6625 · PC2 -0.03334PC1 0.1992 · PC2 0.07783PC1 -0.6054 · PC2 -0.1417PC1 0.4673 · PC2 -0.2491PC1 -0.1285 · PC2 -0.0825PC1 0.1339 · PC2 0.356PC1 -0.4619 · PC2 0.3941PC1 (89.1%)PC2 (7.6%)259 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
10.012954-0.098399
2-0.19572-0.10694
3-0.17725-0.44997
4-0.745380.043093
5-0.46250.25243
6-0.42297-0.30522
7-0.308560.1735
8-0.0028520.065945
9-0.324810.16802
100.5663-0.059544
11-0.488680.025634
12-0.44701-0.0022311
130.5431-0.60286
14-0.068951-0.0016351
150.24166-0.27642
16-0.0452160.30643
17-0.095181-0.23293
18-0.0218860.077905
19-0.648280.17616
200.273780.31455
21-0.797360.048339
22-0.12597-0.19707
23-1.1076-0.36936
24-0.499250.1643
25-0.3629-0.031324
260.23256-0.072958
270.418290.03373
28-0.459960.14894
290.25839-0.024576
300.76782-0.11695
31-0.0922370.16956
32-0.471680.14709
330.48296-0.20481
34-0.3530.30314
35-0.067186-0.12071
36-0.170480.27118
37-0.167350.37196
38-0.0179730.17954
39-0.0557190.22292
40-0.4396-0.15056
41-0.27375-0.41346
42-0.1655-0.14125
430.60065-0.059644
44-0.356080.25244
450.61954-0.0079437
46-0.37477-0.24976
470.59451-0.060528
48-0.547-0.037196
490.00674130.10154
50-0.23243-0.30332
510.30645-0.44012
52-0.111230.089273
530.10326-0.058082
540.83219-0.061212
550.47497-0.31122
56-0.69962-0.05314
57-0.707960.15065
580.525470.026299
59-0.662590.026134
60-0.036263-0.057428
61-0.420510.21509
620.12365-0.35688
63-0.33661-0.17173
64-0.099-0.12546
65-0.033982-0.30065
66-0.438460.043918
670.0723010.18523
68-1.08370.30806
690.067119-0.18159
700.040963-0.18923
710.15085-0.45072
720.294770.058703
73-0.370860.083771
740.62097-0.028498
750.28204-0.3188
76-0.46850.31906
77-0.402940.0010203
78-0.25866-0.04367
79-0.45113-0.12598
80-0.569060.24687
810.17018-0.25506
823.69310.034742
83-0.10236-0.11578
84-0.14532-0.25535
850.50186-0.046922
86-0.585860.10375
87-0.24456-0.37249
88-0.3649-0.20188
89-0.14717-0.27136
90-0.65824-0.029013
91-0.1959-0.37631
920.13484-0.079133
930.274850.022471
940.20081-0.12901
95-0.57254-0.032341
96-0.514940.020996
97-0.172740.18723
980.74557-0.17534
99-0.42575-0.12285
100-0.426010.097715
101-0.45240.33479
102-0.564760.31764
1030.342750.14196
104-0.685670.1018
105-0.41890.19503
1060.192470.089256
1070.26929-0.14748
108-0.33160.29991
109-0.085839-0.18443
110-0.496250.17842
111-0.485960.36575
1120.0172120.1625
113-0.0349040.40959
114-0.666010.010319
115-0.37944-0.1946
116-0.585090.14399
117-0.33524-0.011781
118-0.111610.23791
119-0.0654150.10486
120-0.41691-0.28464
121-0.441220.22798
122-0.424820.22926
123-0.41046-0.0031008
124-0.62814-0.32139
125-0.54494-0.31265
126-1.18330.1613
127-0.13241-0.28547
128-0.40469-0.10555
1290.127550.33262
1300.011008-0.24422
131-0.405810.36039
1320.43972-0.2614
1330.125970.15583
1340.036321-0.55784
135-0.471680.0019381
136-0.806780.35699
1370.11412-0.19321
138-0.59880.26902
139-0.95783-0.054342
140-0.40901-0.12273
141-0.580790.2261
1420.32264-0.0558
143-0.59323-0.025747
144-0.522470.53404
145-0.382130.091608
146-0.0634050.14732
1470.0573040.11327
148-0.512240.34758
149-0.308750.13667
150-0.447920.22699
1510.49126-0.064026
152-0.387450.036101
153-0.229570.26642
154-0.835970.3424
155-0.11467-0.3047
1560.086103-0.062359
157-0.259470.15373
158-0.0197210.10152
159-0.471070.12369
1600.333660.018071
161-0.20430.24455
1620.45864-0.053747
1630.414950.11215
164-0.526630.096721
165-0.897490.31856
1660.133480.11901
1670.042913-0.10241
1680.14761-0.02972
1690.17066-0.16001
170-0.0481330.21789
171-0.044810.20879
1720.030705-0.15462
173-0.0697560.17059
174-0.29281-0.2861
175-0.34649-0.19419
176-0.000921790.032805
177-0.0347450.23297
1780.0561620.28666
179-0.51326-0.04329
180-0.42054-0.17944
181-0.0593110.067181
182-0.25768-0.4829
183-0.34755-0.30126
184-0.76092-0.059869
185-0.173660.17251
186-0.39996-0.1262
1870.029587-0.12099
1880.312830.011537
1890.43541-0.036941
1900.54226-0.031279
1910.062502-0.03792
192-0.28591-0.23052
193-0.46060.18243
194-0.116060.050998
195-0.62143-0.15856
1960.122570.042909
197-0.18138-0.41718
1980.976-0.6898
199-0.3848-0.089877
200-0.075569-0.082571
201-0.50667-0.3008
202-0.221290.39162
2030.0739670.48404
204-0.16023-0.18454
205-0.0729580.24726
2060.0056303-0.089169
2070.28145-0.28315
2080.65722-0.26978
209-0.28308-0.016082
2100.66254-0.28827
211-0.320380.38157
212-0.32259-0.0039335
2130.50549-0.21882
214-0.123160.24347
215-0.0124090.23307
216-0.097017-0.33213
217-0.390760.13618
2180.30991-0.13444
219-0.774630.38581
2200.59555-0.14298
2210.29606-0.50826
2220.4286-0.07115
2230.42785-0.34991
2243.6640.17201
2253.34990.6876
2263.79420.10495
227-0.34314-0.073822
2280.373310.098587
2290.138210.12707
230-0.196640.11237
231-0.17847-0.27145
2320.023713-0.28092
2330.34981-0.20991
234-0.117920.24658
2353.47430.27326
2363.493-0.14923
2373.76230.33012
2380.000413220.18144
2393.63510.19953
2400.33211-0.074435
241-0.554760.0091289
2420.18193-0.068038
243-0.0351060.064421
2443.14640.26961
245-0.748750.19779
246-0.356760.53248
2470.47465-0.2324
2480.66981-0.18907
2490.1459-0.012438
250-0.093212-0.13177
251-0.031751-0.12902
2520.0969930.024144
253-0.66249-0.033342
2540.199210.077827
255-0.60541-0.14165
2560.46727-0.24907
257-0.12854-0.082504
2580.133940.35596
259-0.461940.39414

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: 89.1% (cumulative 89.1%)1PC2: 7.6% (cumulative 96.6%)2PC3: 3.0% (cumulative 99.7%)3PC4: 0.2% (cumulative 99.8%)4PC5: 0.1% (cumulative 99.9%)5PC6: 0.0% (cumulative 99.9%)6PC7: 0.0% (cumulative 100.0%)7PC8: 0.0% (cumulative 100.0%)8PC9: 0.0% (cumulative 100.0%)9PC10: 0.0% (cumulative 100.0%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
View explained variance values
Variance per displayed principal component
ComponentSpectral variance
PC189.06%
PC27.57%
PC33.05%
PC40.16%
PC50.07%
PC60.03%
PC70.02%
PC80.01%
PC90.00%
PC100.00%
X-Y spectral correlation 4

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 chloride_average

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

X_nirs_g1 · chloride_average spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation7501,0001,2501,5001,750|r|signed raxis · Pearson correlation scale

Spectral association with chloridometer_reading1

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

X_nirs_g1 · chloridometer_reading1 spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation7501,0001,2501,5001,750|r|signed raxis · Pearson correlation scale

Spectral association with chloridometer_reading2

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

X_nirs_g1 · chloridometer_reading2 spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation7501,0001,2501,5001,750|r|signed raxis · Pearson correlation scale
Targetmax |r|axis @ maxmean |r||r| ≥ .5
chloride_average0.2441,6860.03220.0%
chloridometer_reading10.2471,6860.03070.0%
chloridometer_reading20.2481,6860.03180.0%
chloridometer_reading30.2481,6860.0310.0%

X_svc_hr1024i

X_svc_hr1024i · NIR · SVC HR-1024i

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

Spectral signal summary

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

X_svc_hr1024i spectra020406001,0002,0003,000q05-q95 envelopeq25-q75 envelopemedian spectrummedianq25–q75q05–q95wavelength / nm339nm — median 9.94 (q25–q75 7.665–12.22)355nm — median 6.562 (q25–q75 5.425–7.711)370nm — median 5.012 (q25–q75 4.309–5.671)386nm — median 4.404 (q25–q75 3.905–4.993)402nm — median 4.087 (q25–q75 3.655–4.609)417nm — median 4.017 (q25–q75 3.574–4.461)433nm — median 4.032 (q25–q75 3.579–4.447)449nm — median 4.044 (q25–q75 3.588–4.494)464nm — median 4.12 (q25–q75 3.683–4.561)480nm — median 4.205 (q25–q75 3.75–4.651)496nm — median 4.429 (q25–q75 3.967–4.905)511nm — median 5.305 (q25–q75 4.739–5.979)527nm — median 8.518 (q25–q75 7.352–10.21)543nm — median 10.57 (q25–q75 9.024–12.73)558nm — median 10.74 (q25–q75 9.156–12.95)574nm — median 8.412 (q25–q75 7.156–10.2)589nm — median 6.982 (q25–q75 6.031–8.361)605nm — median 6.434 (q25–q75 5.598–7.631)621nm — median 5.574 (q25–q75 4.971–6.497)636nm — median 5.331 (q25–q75 4.757–6.157)652nm — median 4.692 (q25–q75 4.212–5.239)668nm — median 4.379 (q25–q75 3.928–4.821)683nm — median 4.802 (q25–q75 4.346–5.328)699nm — median 9.764 (q25–q75 8.492–11.53)715nm — median 24.3 (q25–q75 21.78–27.37)730nm — median 37.43 (q25–q75 35.46–39.83)746nm — median 44.76 (q25–q75 43–46.83)762nm — median 46.71 (q25–q75 44.9–48.93)777nm — median 47.03 (q25–q75 45.24–49.26)793nm — median 47.18 (q25–q75 45.37–49.37)809nm — median 47.28 (q25–q75 45.42–49.41)824nm — median 47.31 (q25–q75 45.47–49.45)840nm — median 47.34 (q25–q75 45.49–49.48)856nm — median 47.37 (q25–q75 45.51–49.55)871nm — median 47.38 (q25–q75 45.53–49.55)887nm — median 47.32 (q25–q75 45.45–49.55)903nm — median 47.28 (q25–q75 45.42–49.53)918nm — median 47.24 (q25–q75 45.41–49.46)934nm — median 47.06 (q25–q75 45.2–49.27)950nm — median 46.67 (q25–q75 44.79–48.88)965nm — median 46.15 (q25–q75 44.33–48.33)981nm — median 46.08 (q25–q75 44.23–48.24)996nm — median 46.06 (q25–q75 44.31–48.22)1,012nm — median 45.86 (q25–q75 44.09–48.09)1,028nm — median 45.99 (q25–q75 44.33–48.23)1,043nm — median 46.16 (q25–q75 44.43–48.31)1,059nm — median 46.26 (q25–q75 44.49–48.39)1,075nm — median 46.27 (q25–q75 44.49–48.41)1,090nm — median 46.24 (q25–q75 44.46–48.41)1,106nm — median 46.07 (q25–q75 44.27–48.23)1,122nm — median 45.8 (q25–q75 44.03–47.97)1,137nm — median 45.09 (q25–q75 43.36–47.24)1,153nm — median 43.66 (q25–q75 41.91–45.75)1,169nm — median 43.05 (q25–q75 41.43–45.13)1,184nm — median 42.89 (q25–q75 41.29–44.93)1,200nm — median 42.81 (q25–q75 41.26–44.86)1,216nm — median 42.94 (q25–q75 41.35–45.01)1,231nm — median 43.1 (q25–q75 41.51–45.21)1,247nm — median 43.31 (q25–q75 41.71–45.41)1,263nm — median 43.33 (q25–q75 41.72–45.48)1,278nm — median 43.22 (q25–q75 41.6–45.35)1,294nm — median 42.88 (q25–q75 41.26–45.01)1,310nm — median 42.13 (q25–q75 40.52–44.22)1,325nm — median 40.92 (q25–q75 39.19–42.88)1,341nm — median 39.23 (q25–q75 37.43–41.15)1,357nm — median 37.49 (q25–q75 35.73–39.29)1,372nm — median 35.18 (q25–q75 33.56–36.97)1,388nm — median 29.14 (q25–q75 27.61–30.87)1,404nm — median 20.82 (q25–q75 19.34–22.45)1,419nm — median 16.5 (q25–q75 15.03–17.91)1,435nm — median 14.93 (q25–q75 13.52–16.31)1,450nm — median 14.6 (q25–q75 13.28–16.15)1,466nm — median 15.12 (q25–q75 13.75–16.75)1,482nm — median 16.65 (q25–q75 15.2–18.39)1,497nm — median 18.62 (q25–q75 17.07–20.34)1,513nm — median 20.78 (q25–q75 19.12–22.56)1,529nm — median 22.87 (q25–q75 21.17–24.62)1,544nm — median 24.62 (q25–q75 22.95–26.37)1,560nm — median 26.21 (q25–q75 24.61–27.92)1,576nm — median 27.56 (q25–q75 25.96–29.2)1,591nm — median 28.62 (q25–q75 27.04–30.27)1,607nm — median 29.48 (q25–q75 27.92–31.16)1,623nm — median 30.26 (q25–q75 28.62–31.92)1,638nm — median 30.78 (q25–q75 29.15–32.42)1,654nm — median 31.14 (q25–q75 29.46–32.79)1,670nm — median 31.2 (q25–q75 29.53–32.85)1,685nm — median 31.01 (q25–q75 29.4–32.71)1,701nm — median 30.5 (q25–q75 28.97–32.16)1,717nm — median 29.9 (q25–q75 28.33–31.51)1,732nm — median 29.2 (q25–q75 27.61–30.75)1,748nm — median 28.35 (q25–q75 26.74–29.88)1,764nm — median 27.3 (q25–q75 25.73–28.85)1,779nm — median 26.63 (q25–q75 25.11–28.14)1,795nm — median 26.36 (q25–q75 24.85–27.89)1,811nm — median 26.35 (q25–q75 24.81–27.85)1,826nm — median 26.26 (q25–q75 24.75–27.78)1,842nm — median 25.56 (q25–q75 24.04–27.08)1,858nm — median 23.12 (q25–q75 21.74–24.76)1,873nm — median 17.83 (q25–q75 16.43–19.23)1,889nm — median 9.934 (q25–q75 8.934–11.1)1,904nm — median 5.825 (q25–q75 5.218–6.549)1,920nm — median 3.789 (q25–q75 3.353–4.343)1,936nm — median 3.807 (q25–q75 3.35–4.351)1,951nm — median 4.122 (q25–q75 3.606–4.695)1,967nm — median 4.705 (q25–q75 4.082–5.395)1,983nm — median 5.51 (q25–q75 4.748–6.311)1,998nm — median 6.413 (q25–q75 5.56–7.327)2,014nm — median 7.498 (q25–q75 6.548–8.539)2,030nm — median 8.572 (q25–q75 7.511–9.753)2,045nm — median 9.512 (q25–q75 8.388–10.76)2,061nm — median 10.43 (q25–q75 9.303–11.76)2,077nm — median 11.46 (q25–q75 10.28–12.76)2,092nm — median 12.36 (q25–q75 11.11–13.76)2,108nm — median 13.29 (q25–q75 11.98–14.68)2,124nm — median 14.14 (q25–q75 12.82–15.61)2,139nm — median 14.79 (q25–q75 13.46–16.26)2,155nm — median 15.3 (q25–q75 13.94–16.76)2,171nm — median 15.63 (q25–q75 14.23–17.06)2,186nm — median 15.95 (q25–q75 14.48–17.35)2,202nm — median 16.22 (q25–q75 14.74–17.58)2,218nm — median 16.33 (q25–q75 14.88–17.69)2,233nm — median 16.18 (q25–q75 14.75–17.6)2,249nm — median 15.67 (q25–q75 14.26–17.01)2,265nm — median 14.78 (q25–q75 13.41–16.11)2,280nm — median 14 (q25–q75 12.67–15.27)2,296nm — median 13.25 (q25–q75 11.95–14.52)2,311nm — median 12.46 (q25–q75 11.23–13.72)2,327nm — median 11.77 (q25–q75 10.57–13.04)2,343nm — median 11.04 (q25–q75 9.884–12.26)2,358nm — median 10.33 (q25–q75 9.268–11.51)2,374nm — median 9.614 (q25–q75 8.57–10.77)2,390nm — median 8.885 (q25–q75 7.902–9.962)2,405nm — median 8.214 (q25–q75 7.272–9.205)2,421nm — median 7.477 (q25–q75 6.575–8.385)2,437nm — median 6.744 (q25–q75 5.938–7.595)2,452nm — median 6.142 (q25–q75 5.441–6.946)2,468nm — median 5.605 (q25–q75 4.92–6.361)2,484nm — median 5.2 (q25–q75 4.558–5.87)2,499nm — median 4.899 (q25–q75 4.288–5.561)2,515nm — median 4.985 (q25–q75 4.269–5.732)

Sampling

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

Wavelengths
?Number of spectral channels. A channel can represent wavelength, wavenumber or another feature axis.
2,177
Axis range
?Lowest and highest recorded spectral-axis coordinates, in the stated unit.
339–2,515 nm
Mean spacing
?Average difference between adjacent spectral-axis coordinates; compare only within the same unit.
1 nm
Grid
?Uniform means adjacent axis spacings are approximately equal. An irregular grid may need care when applying derivatives.
uniform
Observations
?Exported spectral rows in this source, including repeated measurements when present.
556

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.
-0.355 – 68.2
Mean range
?Minimum and maximum of the mean spectrum across spectral channels.
3.86 – 47.7
Mean level
?Average signal over observations and channels. The historical key mean_reflectance may also store other signal representations.
23.52
Area
?Trapezoidal integral of the mean spectrum over the sorted recorded axis; its unit is signal multiplied by axis unit.
5.119e+04
PTP
?Peak-to-peak: maximum minus minimum of the mean spectrum. Low values indicate little variation along the mean spectrum.
43.85
Noise RMS
?Historical roughness sigma proxy from robust second differences. Narrow genuine bands can also raise it; this is not repeat-measured instrument noise.
0.0025609
Roughness S/N proxy
?Average absolute signal divided by the roughness proxy. Higher means smoother signal relative to its amplitude, not certified instrument SNR.
9.2e+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.
43.8
Smoothness
?Mean per-spectrum RMS of second differences, in signal units. Smaller values indicate smoother spectra under this protocol.
0.2903
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.
92

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.
130,139
Spike rate
?Fraction of tested second-difference positions flagged as spikes, displayed as a percentage.
10.76%
Jump count
?Adjacent-channel changes flagged by the first-difference heuristic, potentially including detector joins.
56,740
Jump rate
?Fraction of tested adjacent-channel differences flagged as jumps, displayed as a percentage.
4.69%
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.
-14.921
Curvature RMS
?Median per-spectrum RMS of second differences, summarizing curvature and high-frequency variation.
0.28573
D1 RMS
?Median per-spectrum RMS of adjacent-channel first differences; reflects both real spectral structure and artefacts.
0.25817
RMS to mean
?Root mean square distance to this dataset's mean spectrum, in signal units.
1.8285
RMS p95
?95th percentile of distances to the mean spectrum: 95% of observations have a distance at or below this value.
4.4196
SAM to mean
?Spectral Angle Mapper: angle to the mean spectrum, in radians. Smaller angles indicate more similar shapes.
0.036596
SAM p95
?95th percentile of spectral angles to the dataset mean, in radians. It is less sensitive to overall amplitude than RMS.
0.078343
Affine offset p95
?95th percentile of absolute fitted offsets when matching each spectrum to the dataset mean.
2.7678
Affine gain p95 Δ
?95th percentile of the absolute gain deviation from 1 in the fit to the mean spectrum.
0.1557
Affine residual p95
?95th percentile of residual RMS after gain and offset correction to the mean spectrum.
1.5556
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.
2.3
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.
3.7
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.
1.9
Repeat groups
?Number of IDs with several observations. Source documentation is needed to decide whether these are technical repeats, positions or time points.
0

Dimensionality (PCA)

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

Effective rank
?Entropy-based summary of the variance distribution across components. Larger values indicate variation spread across more dimensions.
2.3
PCs → 95% var
?Number of principal components needed to explain 95% of spectral variance, when reached by the computed projection.
3
PCs → 99% var
?Number of principal components needed to explain 99% of spectral variance, when reached by the computed projection.
9
Top-10 cum. var
?Fraction of spectral variance explained by up to the first ten computed principal components, displayed as a percentage.
99.2%
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		0.000165%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		23.5150.68mediumAtypical 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		511850.68mediumAtypical 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		43.8470.00weakStrong 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		262.760.00weakNormal 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		0.00256090.00weakStableLamp, 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		9182.50.00weakGood signalAcquisitionmean(abs(X)) / noise_rmsalert decreases with SNR dB; >=40 dB is treated as low alert
NoiseBandwise roughness S/N proxy
?Minimum channel-wise ratio of absolute mean signal to local second-difference roughness. A smaller ratio identifies a weak or rough spectral region; genuine narrow bands and near-zero signal can also lower it. This is not certified instrument SNR. Scoring: alert decreases with worst-band SNR dB; >=35 dB is treated as low alert. Higher alert scores indicate stronger heuristic concern, not a fault probability or an acceptance decision. A dash means unavailable.
noise.bandwise_roughness_signal_to_noise_proxy_min		8.07970.48mediumProblem areaDetectormin(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		130,1391.00strongArtifactsCosmic 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		10.8%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		56,7401.00strongDetector 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		4.69%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		0.000165%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		-14.9210.68mediumDriftIlluminationlinear 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		0.285730.65mediumUnusual shapeBackground, 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		0.258170.12weakFlatBiology 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		2.34370.29weakCompliantArtifact, 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		3.70140.46mediumExtreme 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		1.92390.48mediumGlobal 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		4.41960.40weakTypicalDomain 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		0.0783430.22weakSimilarBackground, 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		0.0493330.84strongSubpopulationsDifferent 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		2.51070.76strongIsolated 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		0.563620.84strongAtypical spectrumVarious causesp95 IsolationForest anomaly score on PCA scoresalert follows structure complexity; raw score is implementation-dependent

PCA score plot — explore spectral variation

Source X_svc_hr1024i: 556 of 556 source observations are plotted. PC1 captures 73.5% and PC2 19.4% of the reported spectral variance: 93.0% together; 7.0% 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.

X_svc_hr1024i PCA score plot-400-2000200400600-300-200-1000100200PC1 -87.68 · PC2 -5.271PC1 365.5 · PC2 -55.71PC1 174.5 · PC2 36.49PC1 -49.98 · PC2 63.03PC1 -192 · PC2 9.905PC1 157.5 · PC2 63.62PC1 33.87 · PC2 -62.53PC1 -158.7 · PC2 -16.88PC1 -9.3 · PC2 52.12PC1 59.91 · PC2 31.59PC1 -152.1 · PC2 33.42PC1 70.25 · PC2 40.6PC1 -138 · PC2 -7.082PC1 -130.4 · PC2 85.45PC1 185.9 · PC2 -41.83PC1 -133.2 · PC2 35.69PC1 189.2 · PC2 65.22PC1 14.66 · PC2 -33.34PC1 185.9 · PC2 -34.69PC1 -162 · PC2 50.49PC1 -89.81 · PC2 72.96PC1 -32.44 · PC2 9.845PC1 -64.46 · PC2 71.82PC1 180.4 · PC2 20.05PC1 4.375 · PC2 42.03PC1 9.2 · PC2 -14.76PC1 -127.9 · PC2 28.32PC1 -30.71 · PC2 30.22PC1 -19.49 · PC2 50.15PC1 56.54 · PC2 20.14PC1 101 · PC2 80.88PC1 -67.09 · PC2 -36.49PC1 -45.51 · PC2 -41.95PC1 -137.1 · PC2 50.03PC1 -57.5 · PC2 23.15PC1 -124 · PC2 57.26PC1 21.13 · PC2 -21.23PC1 132.3 · PC2 33.26PC1 -64.16 · PC2 52.99PC1 -7.919 · PC2 19.57PC1 35.79 · PC2 47.3PC1 -21.49 · PC2 76.72PC1 -67.77 · PC2 43.03PC1 -44.88 · PC2 12.23PC1 -23.29 · PC2 -37.69PC1 -98.06 · PC2 30.85PC1 -68.16 · PC2 -6.981PC1 -10.89 · PC2 -70.37PC1 78.24 · PC2 43.46PC1 -55.47 · PC2 88.93PC1 354.5 · PC2 68.58PC1 -78.83 · PC2 20.63PC1 272.1 · PC2 23.23PC1 166.4 · PC2 88.67PC1 4.821 · PC2 -4.659PC1 -49.33 · PC2 61.26PC1 103.2 · PC2 -41.19PC1 -84.64 · PC2 -43.4PC1 -65.18 · PC2 86.11PC1 26.45 · PC2 -26.09PC1 -62.17 · PC2 94.47PC1 105.4 · PC2 -23.09PC1 6.429 · PC2 -10.69PC1 93.88 · PC2 50.22PC1 59.93 · PC2 6.078PC1 72.98 · PC2 -58.9PC1 91.83 · PC2 30.46PC1 413.7 · PC2 88.68PC1 -112.7 · PC2 -73.07PC1 -7.76 · PC2 64.23PC1 54.23 · PC2 36.58PC1 63.5 · PC2 120PC1 -38.52 · PC2 1.623PC1 37.66 · PC2 -15.15PC1 -18.3 · PC2 27.63PC1 57.61 · PC2 71.55PC1 -41.68 · PC2 -8.131PC1 59.67 · PC2 31.82PC1 -145.1 · PC2 57.03PC1 123 · PC2 -5.701PC1 -47.98 · PC2 67.04PC1 -28.77 · PC2 99.27PC1 -106.4 · PC2 -25.47PC1 11.98 · PC2 -72.61PC1 -91.46 · PC2 0.8527PC1 135 · PC2 -5.804PC1 -2.488 · PC2 -7.242PC1 -19.9 · PC2 28.18PC1 137.3 · PC2 50.37PC1 41.08 · PC2 -29.78PC1 258 · PC2 30.87PC1 -124.3 · PC2 -2.608PC1 -130.7 · PC2 46.83PC1 -49.41 · PC2 81.05PC1 -10.58 · PC2 -1.536PC1 -118.8 · PC2 79.39PC1 103.2 · PC2 37.01PC1 10.67 · PC2 108.4PC1 -17.21 · PC2 14.14PC1 -56.39 · PC2 32.57PC1 -97.52 · PC2 11.76PC1 -59.46 · PC2 10.01PC1 -74.28 · PC2 11.47PC1 -20.46 · PC2 -5.041PC1 -21.13 · PC2 -31.88PC1 -51.33 · PC2 41.87PC1 99.66 · PC2 -14.03PC1 -4.786 · PC2 63.6PC1 -169.8 · PC2 9.689PC1 0.1468 · PC2 37PC1 -18.99 · PC2 10.68PC1 51.93 · PC2 54.59PC1 -44.94 · PC2 54.64PC1 64.29 · PC2 80.29PC1 137.4 · PC2 -20.84PC1 111.1 · PC2 62.54PC1 -70.57 · PC2 78.26PC1 -86.14 · PC2 50.6PC1 -74.22 · PC2 97.59PC1 2.564 · PC2 30.75PC1 -2.705 · PC2 31.8PC1 -94.8 · PC2 40.45PC1 -191.6 · PC2 -13.63PC1 -55.75 · PC2 -5.21PC1 -89.85 · PC2 87.58PC1 -62.29 · PC2 39.93PC1 61.67 · PC2 34.07PC1 39.76 · PC2 28.3PC1 70.89 · PC2 18.81PC1 211 · PC2 45.03PC1 -43.49 · PC2 -10.86PC1 36.86 · PC2 68.39PC1 -94.45 · PC2 70.17PC1 122 · PC2 -0.02191PC1 282.7 · PC2 117.2PC1 -46.31 · PC2 68.91PC1 -18.87 · PC2 -29.89PC1 -53.24 · PC2 0.8925PC1 32.5 · PC2 -87.99PC1 -15.54 · PC2 -25.35PC1 37.59 · PC2 -14.88PC1 -55.62 · PC2 44.53PC1 -31.17 · PC2 45.71PC1 -68.08 · PC2 28.52PC1 8.618 · PC2 11.06PC1 -62.35 · PC2 7.384PC1 -10.84 · PC2 54.86PC1 24.49 · PC2 6.927PC1 215.6 · PC2 50.19PC1 20.53 · PC2 21.82PC1 -104.4 · PC2 8.738PC1 39.59 · PC2 52.56PC1 -89.89 · PC2 24.52PC1 -57.47 · PC2 55.84PC1 2.834 · PC2 45.48PC1 -262.9 · PC2 10.43PC1 -155.1 · PC2 5.273PC1 129 · PC2 107.7PC1 -59.66 · PC2 40.33PC1 20.6 · PC2 40.14PC1 -53.13 · PC2 -8.065PC1 -40.11 · PC2 -8.597PC1 111.2 · PC2 71.43PC1 33.38 · PC2 -37.39PC1 36.57 · PC2 98.24PC1 65.55 · PC2 -10.26PC1 -55.83 · PC2 4.216PC1 76.76 · PC2 -76.74PC1 -25.59 · PC2 -70.96PC1 -26.74 · PC2 19.01PC1 -154.6 · PC2 -11.09PC1 44.28 · PC2 -113.5PC1 105.8 · PC2 76.46PC1 15.69 · PC2 40.41PC1 -57.31 · PC2 -35.36PC1 -68.95 · PC2 59.1PC1 17.51 · PC2 93.95PC1 -52.28 · PC2 -18.76PC1 -165.5 · PC2 22.79PC1 -118.5 · PC2 29.77PC1 -133.3 · PC2 4.839PC1 -151.3 · PC2 -69.22PC1 -168.4 · PC2 50.9PC1 -166.2 · PC2 8.665PC1 -58.75 · PC2 -79.99PC1 -216.9 · PC2 -77.7PC1 -28.55 · PC2 43.97PC1 -130.6 · PC2 9.082PC1 -155.7 · PC2 36.26PC1 -187.5 · PC2 -6.725PC1 -246.1 · PC2 -33.74PC1 -29.16 · PC2 36.4PC1 -77.29 · PC2 4.734PC1 -99.13 · PC2 1.296PC1 -201.5 · PC2 -63.48PC1 -216.1 · PC2 28.42PC1 -180.2 · PC2 -44.2PC1 -166.3 · PC2 26.71PC1 -21.88 · PC2 46.44PC1 -65.58 · PC2 58.39PC1 -17.92 · PC2 65.42PC1 -103.6 · PC2 -10.84PC1 -42.42 · PC2 59.38PC1 -109.2 · PC2 20.75PC1 -91.9 · PC2 112.1PC1 -26.65 · PC2 32.75PC1 -54.57 · PC2 33.19PC1 -40.32 · PC2 40.32PC1 -0.1837 · PC2 17.18PC1 -127.6 · PC2 64.95PC1 -136.7 · PC2 64.63PC1 -34.24 · PC2 26.61PC1 94.57 · PC2 69.12PC1 -48.23 · PC2 21.08PC1 33.35 · PC2 19.71PC1 -30.72 · PC2 11.07PC1 -101.2 · PC2 -12.4PC1 -90.2 · PC2 71.55PC1 -64.5 · PC2 63.28PC1 26.45 · PC2 0.7801PC1 -52.6 · PC2 -9.746PC1 133 · PC2 34.47PC1 52.23 · PC2 -0.3345PC1 14.51 · PC2 58.16PC1 -11.91 · PC2 120.8PC1 -74.9 · PC2 34.54PC1 -29 · PC2 44.92PC1 10.24 · PC2 32.37PC1 46.1 · PC2 -8.52PC1 -31.52 · PC2 -1.316PC1 -53.24 · PC2 76.58PC1 31.3 · PC2 37.72PC1 -103.4 · PC2 10.63PC1 -210.3 · PC2 95.59PC1 -104.4 · PC2 16.54PC1 8.119 · PC2 79.68PC1 0.1455 · PC2 99.48PC1 117.7 · PC2 81.92PC1 64.83 · PC2 49.52PC1 18.26 · PC2 -38.88PC1 -138.3 · PC2 41.42PC1 -74.14 · PC2 -37.85PC1 -155.3 · PC2 28.13PC1 -85.16 · PC2 30.19PC1 -34.57 · PC2 77.46PC1 -46.77 · PC2 -21.25PC1 -98.72 · PC2 -18.84PC1 -90.3 · PC2 67.06PC1 -15.42 · PC2 -4.351PC1 -162 · PC2 35.98PC1 -52.46 · PC2 63.26PC1 -28.72 · PC2 83.4PC1 -113.5 · PC2 39.83PC1 -75.82 · PC2 51.99PC1 116.7 · PC2 84PC1 69.76 · PC2 26.48PC1 45.22 · PC2 91.62PC1 -36.61 · PC2 2.922PC1 5.615 · PC2 -29.4PC1 126.9 · PC2 13.05PC1 -67.27 · PC2 -15.98PC1 155 · PC2 -54.03PC1 73.42 · PC2 -40.79PC1 -65.75 · PC2 56.44PC1 -152.2 · PC2 69.39PC1 56.99 · PC2 -23.62PC1 -61.84 · PC2 -79.32PC1 48.65 · PC2 1.585PC1 -98.33 · PC2 -60.47PC1 81.66 · PC2 -28.6PC1 88.51 · PC2 27.96PC1 9.97 · PC2 -8.55PC1 -19.24 · PC2 -12.36PC1 24.88 · PC2 -28.89PC1 119.6 · PC2 -39.78PC1 20.98 · PC2 -5.098PC1 3.479 · PC2 -81.16PC1 -17.81 · PC2 -9.798PC1 283.9 · PC2 25.53PC1 -10.93 · PC2 -24PC1 -83.58 · PC2 20.5PC1 60.24 · PC2 -68.96PC1 7.037 · PC2 26.17PC1 50.09 · PC2 -107.5PC1 -70.74 · PC2 -11.66PC1 -80.3 · PC2 62.72PC1 39.33 · PC2 -10.98PC1 25.67 · PC2 -14.41PC1 156.9 · PC2 -39.44PC1 63.79 · PC2 -17.45PC1 -13.68 · PC2 -48.78PC1 99.85 · PC2 -51.24PC1 147.4 · PC2 57.55PC1 -10.64 · PC2 -32.35PC1 123.8 · PC2 -221.9PC1 60.73 · PC2 1.091PC1 93.17 · PC2 26.07PC1 208.3 · PC2 -81.1PC1 9.466 · PC2 -15.23PC1 84.08 · PC2 -13.08PC1 -4.192 · PC2 -21.15PC1 21.73 · PC2 -71.33PC1 70.75 · PC2 -69.58PC1 -21.73 · PC2 -15.24PC1 300.1 · PC2 -3.914PC1 -54.5 · PC2 -49.37PC1 156.2 · PC2 -12.93PC1 -115.3 · PC2 -9.843PC1 42.24 · PC2 14.74PC1 6.201 · PC2 30.87PC1 98.89 · PC2 42.38PC1 83.09 · PC2 58.39PC1 -111.6 · PC2 -59.78PC1 -71.79 · PC2 -38.59PC1 77.38 · PC2 -98.35PC1 47.31 · PC2 -56.43PC1 12.37 · PC2 60.55PC1 19.71 · PC2 -72.5PC1 42.08 · PC2 -22.87PC1 -42.42 · PC2 -64.24PC1 -92.75 · PC2 -87.28PC1 -235.4 · PC2 -108PC1 -54.18 · PC2 -75.97PC1 88.07 · PC2 28.05PC1 -69.49 · PC2 8.145PC1 63.49 · PC2 56.84PC1 39.36 · PC2 27.07PC1 -21.59 · PC2 -2.255PC1 13.03 · PC2 -32.99PC1 102.7 · PC2 -31.4PC1 61.14 · PC2 32.55PC1 -109.1 · PC2 96.3PC1 23.71 · PC2 -48.54PC1 -24.6 · PC2 10.65PC1 152.6 · PC2 11.51PC1 182.7 · PC2 -41.61PC1 -26.25 · PC2 -23.21PC1 14.46 · PC2 -39.76PC1 26.14 · PC2 -19.7PC1 29.15 · PC2 -27.15PC1 228 · PC2 -1.112PC1 9.123 · PC2 -2.467PC1 206.6 · PC2 -50.79PC1 144.3 · PC2 -39.25PC1 -76.47 · PC2 -15.83PC1 -58.1 · PC2 -56.15PC1 -58.41 · PC2 -55.43PC1 -13.08 · PC2 -84.39PC1 -32.85 · PC2 -50.6PC1 67.48 · PC2 14.93PC1 -99.65 · PC2 -78.25PC1 8.096 · PC2 13.62PC1 30.42 · PC2 -26.22PC1 -74.47 · PC2 -5.941PC1 66.4 · PC2 -105.7PC1 6.883 · PC2 -16.19PC1 -2.395 · PC2 -53.26PC1 59.66 · PC2 -14.52PC1 -111.9 · PC2 -55.44PC1 -11.44 · PC2 60.83PC1 -35.79 · PC2 -28.26PC1 149.5 · PC2 -99.56PC1 53.75 · PC2 47.56PC1 -69.48 · PC2 5.454PC1 13.5 · PC2 -53.33PC1 -6.322 · PC2 -55.95PC1 -51.68 · PC2 4.405PC1 22.12 · PC2 79.71PC1 200.9 · PC2 34.08PC1 9.053 · PC2 6.889PC1 143.4 · PC2 -79.13PC1 102.6 · PC2 -38.84PC1 225.6 · PC2 -102.6PC1 29.5 · PC2 -73.44PC1 -72.91 · PC2 23.12PC1 -4.073 · PC2 36.87PC1 -68.36 · PC2 38.2PC1 41.03 · PC2 -43.66PC1 37.98 · PC2 -12.93PC1 15.82 · PC2 -2.696PC1 -66.49 · PC2 -19.51PC1 -24.83 · PC2 -7.905PC1 99.27 · PC2 -11.88PC1 58.79 · PC2 20.72PC1 -24.78 · PC2 -15.34PC1 -36.1 · PC2 12.07PC1 96.49 · PC2 -57.8PC1 -39.12 · PC2 -88.08PC1 14.4 · PC2 -62.28PC1 149.5 · PC2 -21.54PC1 127 · PC2 -3.983PC1 -96.74 · PC2 49.77PC1 -125.1 · PC2 -55.33PC1 42.47 · PC2 -19.21PC1 34.5 · PC2 -39.11PC1 -2.776 · PC2 -58.71PC1 27.56 · PC2 -81.51PC1 -91.88 · PC2 -21.16PC1 90.38 · PC2 49.62PC1 -2.054 · PC2 -93.91PC1 75.52 · PC2 -27.93PC1 79.53 · PC2 17.75PC1 -6.231 · PC2 -63.1PC1 131 · PC2 0.1988PC1 120.7 · PC2 -149.8PC1 32.56 · PC2 -125.3PC1 -126.1 · PC2 -20.65PC1 37.76 · PC2 -100.1PC1 -87.95 · PC2 -68.63PC1 44.83 · PC2 -108.6PC1 123.7 · PC2 -61.18PC1 13.99 · PC2 -46.68PC1 -22.53 · PC2 -10.45PC1 87.28 · PC2 -48.75PC1 187.6 · PC2 15.71PC1 -4.368 · PC2 -28.86PC1 -19.47 · PC2 -37.07PC1 -53.56 · PC2 25.67PC1 5.112 · PC2 -5.108PC1 61.19 · PC2 -17.23PC1 96.84 · PC2 -63.11PC1 46.68 · PC2 -2.131PC1 52.96 · PC2 -21.33PC1 74.86 · PC2 12.97PC1 -66.46 · PC2 -35.64PC1 231.4 · PC2 -24.74PC1 43.77 · PC2 -13.3PC1 44.96 · PC2 -6.217PC1 48.9 · PC2 -101.9PC1 -46.67 · PC2 -17.47PC1 45.24 · PC2 -19.77PC1 -3.765 · PC2 -23.2PC1 -70.42 · PC2 -86.32PC1 59.26 · PC2 -0.315PC1 2.367 · PC2 26.82PC1 479.9 · PC2 145PC1 43.81 · PC2 -47.7PC1 99.23 · PC2 -53.51PC1 46.43 · PC2 -63.34PC1 142.5 · PC2 -62.54PC1 117 · PC2 -11.32PC1 -104.1 · PC2 -58.23PC1 -67.81 · PC2 -32.36PC1 -161.5 · PC2 -57.6PC1 17.91 · PC2 -71.61PC1 -20.14 · PC2 62.05PC1 1.632 · PC2 -5.876PC1 -40.14 · PC2 -14.78PC1 -127.8 · PC2 -33.21PC1 -42.76 · PC2 -61.41PC1 -116.6 · PC2 21.88PC1 93.93 · PC2 -34.33PC1 -57.44 · PC2 -8.269PC1 -53.71 · PC2 34.68PC1 114 · PC2 -40.55PC1 72.48 · PC2 -19.88PC1 -43.83 · PC2 -14.71PC1 156.1 · PC2 -55.55PC1 -84.83 · PC2 -8.297PC1 161.2 · PC2 25.76PC1 -2.12 · PC2 -35.67PC1 -27.87 · PC2 -60.17PC1 53.18 · PC2 29.99PC1 188.8 · PC2 2.484PC1 24.51 · PC2 -77.04PC1 -70.33 · PC2 79.31PC1 39.04 · PC2 34.9PC1 -34.45 · PC2 -10.02PC1 25.69 · PC2 -119.4PC1 -116.8 · PC2 -46.02PC1 32.97 · PC2 31.69PC1 -130.3 · PC2 1.494PC1 -83.86 · PC2 -60.1PC1 -105.8 · PC2 -33.1PC1 -21.91 · PC2 -50.24PC1 -39.99 · PC2 -5.13PC1 -98.16 · PC2 -86.31PC1 -111 · PC2 -57.43PC1 -49.97 · PC2 -28.75PC1 -41.72 · PC2 8.806PC1 -97.68 · PC2 -71.85PC1 63.5 · PC2 -12PC1 -48.45 · PC2 -18.31PC1 125.9 · PC2 -19.91PC1 110.5 · PC2 63.86PC1 -68.47 · PC2 -74.17PC1 94.74 · PC2 61.75PC1 139.2 · PC2 -56.26PC1 -98.09 · PC2 2.916PC1 0.4006 · PC2 18.05PC1 -58.09 · PC2 -29.2PC1 -41.71 · PC2 43.18PC1 -59.26 · PC2 -20.36PC1 60.21 · PC2 -14.7PC1 -190.2 · PC2 -56.46PC1 28.45 · PC2 68.62PC1 65.16 · PC2 9.866PC1 51.93 · PC2 -62.8PC1 55.07 · PC2 34.52PC1 -36.4 · PC2 -8.338PC1 -34.16 · PC2 -24.64PC1 -3.918 · PC2 -12.85PC1 -29.83 · PC2 -28.3PC1 -51.8 · PC2 50.58PC1 -111 · PC2 -23.29PC1 -27.5 · PC2 -67.83PC1 -75.73 · PC2 -69.33PC1 55.5 · PC2 5.482PC1 55 · PC2 64.31PC1 -14.51 · PC2 21.04PC1 -63.28 · PC2 -24.8PC1 -118.1 · PC2 -2.487PC1 -12.03 · PC2 -31.45PC1 123.5 · PC2 1.679PC1 -114 · PC2 -0.3021PC1 24.48 · PC2 27.06PC1 -6.466 · PC2 -57.4PC1 17.72 · PC2 33.22PC1 162.9 · PC2 162.2PC1 75 · PC2 -30.47PC1 -44.28 · PC2 -72.07PC1 53.55 · PC2 -22.91PC1 -101.6 · PC2 -50.31PC1 -68.43 · PC2 -21.86PC1 -65.55 · PC2 -87.46PC1 9.529 · PC2 -10.98PC1 62.96 · PC2 -23.23PC1 85.56 · PC2 -74.46PC1 81.55 · PC2 11.88PC1 -58.13 · PC2 44.33PC1 -102.6 · PC2 -26.72PC1 39.58 · PC2 44.54PC1 7.854 · PC2 -25.75PC1 -64.83 · PC2 -87.08PC1 308.8 · PC2 -31.45PC1 19.7 · PC2 -32PC1 -121.2 · PC2 -27.57PC1 -75.53 · PC2 16.98PC1 124.3 · PC2 30.68PC1 -90.01 · PC2 -8.016PC1 -130.7 · PC2 22.06PC1 -45.19 · PC2 -13.2PC1 93.97 · PC2 -31.41PC1 53.11 · PC2 -33.37PC1 93.84 · PC2 -59.63PC1 22.03 · PC2 -13.57PC1 20.95 · PC2 -92.55PC1 -91.44 · PC2 -35.82PC1 32.09 · PC2 -66.57PC1 -41.47 · PC2 -89.72PC1 29.36 · PC2 18.11PC1 11.29 · PC2 -66.19PC1 -6.546 · PC2 35.13PC1 -91.69 · PC2 -43.96PC1 0.529 · PC2 -29.6PC1 138 · PC2 -66.79PC1 (73.5%)PC2 (19.4%)556 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
1-87.679-5.2708
2365.52-55.707
3174.5236.493
4-49.97763.033
5-191.979.9053
6157.5363.616
733.872-62.526
8-158.68-16.885
9-9.299652.118
1059.9131.588
11-152.0633.416
1270.25140.601
13-137.96-7.0823
14-130.3885.449
15185.87-41.826
16-133.2335.685
17189.2465.224
1814.661-33.337
19185.89-34.687
20-16250.491
21-89.80672.956
22-32.4419.8446
23-64.45871.817
24180.420.054
254.374842.027
269.1998-14.759
27-127.928.318
28-30.70830.223
29-19.48650.153
3056.54120.137
31100.9780.879
32-67.092-36.493
33-45.514-41.953
34-137.150.035
35-57.49823.154
36-124.0157.256
3721.127-21.232
38132.3433.258
39-64.15852.995
40-7.918719.57
4135.78847.295
42-21.48676.716
43-67.77143.034
44-44.8812.23
45-23.291-37.692
46-98.06430.851
47-68.161-6.9814
48-10.889-70.375
4978.23743.459
50-55.46688.932
51354.568.584
52-78.83420.63
53272.1223.23
54166.4188.667
554.8209-4.6594
56-49.33261.263
57103.23-41.192
58-84.64-43.404
59-65.18386.105
6026.449-26.089
61-62.17594.472
62105.37-23.092
636.4294-10.694
6493.88350.22
6559.9336.078
6672.979-58.896
6791.82930.457
68413.7188.685
69-112.72-73.07
70-7.760264.233
7154.23236.581
7263.496119.96
73-38.5191.6227
7437.66-15.154
75-18.29827.632
7657.6171.549
77-41.682-8.1315
7859.66631.819
79-145.1457.026
80122.99-5.7014
81-47.97567.04
82-28.76799.266
83-106.44-25.471
8411.983-72.606
85-91.4550.85272
86135.05-5.8045
87-2.4876-7.242
88-19.89628.179
89137.2650.371
9041.08-29.781
91258.0430.869
92-124.32-2.6079
93-130.6746.832
94-49.4181.049
95-10.575-1.5355
96-118.8179.385
97103.1937.01
9810.666108.41
99-17.2114.144
100-56.38832.572
101-97.51611.765
102-59.46210.011
103-74.27511.469
104-20.465-5.0406
105-21.126-31.885
106-51.32941.873
10799.664-14.032
108-4.785963.596
109-169.819.6894
1100.1468236.998
111-18.99410.676
11251.9354.593
113-44.93654.642
11464.29480.286
115137.42-20.84
116111.1462.543
117-70.57278.264
118-86.13850.596
119-74.22197.589
1202.564530.746
121-2.704931.797
122-94.79640.454
123-191.59-13.632
124-55.747-5.21
125-89.84787.579
126-62.28939.928
12761.67234.072
12839.76428.297
12970.89118.811
130210.9545.026
131-43.494-10.863
13236.85868.394
133-94.44670.171
134122-0.021912
135282.67117.2
136-46.30668.91
137-18.873-29.887
138-53.2370.89248
13932.495-87.994
140-15.54-25.355
14137.591-14.882
142-55.61844.533
143-31.1745.711
144-68.08128.518
1458.61811.063
146-62.3527.3841
147-10.84154.86
14824.4866.9274
149215.6150.193
15020.52621.816
151-104.398.738
15239.5952.557
153-89.88824.516
154-57.47255.839
1552.833845.483
156-262.9210.429
157-155.145.2731
158128.99107.73
159-59.65740.327
16020.60440.142
161-53.13-8.0648
162-40.109-8.5965
163111.2571.434
16433.381-37.386
16536.57298.243
16665.552-10.258
167-55.8264.2163
16876.76-76.736
169-25.586-70.962
170-26.73819.006
171-154.63-11.085
17244.278-113.51
173105.7776.462
17415.69440.413
175-57.311-35.358
176-68.94659.098
17717.51393.946
178-52.285-18.763
179-165.522.79
180-118.5429.774
181-133.344.8388
182-151.32-69.218
183-168.3750.896
184-166.238.6649
185-58.752-79.991
186-216.94-77.697
187-28.54843.971
188-130.649.0824
189-155.736.263
190-187.46-6.7247
191-246.07-33.742
192-29.15536.404
193-77.2944.7345
194-99.1311.296
195-201.47-63.481
196-216.0928.42
197-180.22-44.201
198-166.3126.711
199-21.87946.441
200-65.57958.392
201-17.91665.424
202-103.59-10.842
203-42.42259.381
204-109.1820.745
205-91.902112.14
206-26.65332.752
207-54.57133.189
208-40.31640.322
209-0.1836917.176
210-127.664.952
211-136.6664.631
212-34.23826.609
21394.56869.121
214-48.23521.085
21533.35219.707
216-30.72411.074
217-101.2-12.4
218-90.20171.547
219-64.49963.275
22026.4460.78006
221-52.602-9.7463
222132.9634.475
22352.232-0.33446
22414.51158.163
225-11.907120.85
226-74.89934.541
227-2944.917
22810.24132.371
22946.103-8.5197
230-31.518-1.3161
231-53.24176.582
23231.29937.719
233-103.4210.63
234-210.3595.588
235-104.4516.545
2368.118979.683
2370.1454899.478
238117.7481.922
23964.83249.516
24018.262-38.88
241-138.3441.416
242-74.143-37.849
243-155.3328.13
244-85.15730.187
245-34.56677.461
246-46.773-21.25
247-98.719-18.836
248-90.30267.064
249-15.424-4.3505
250-162.0135.982
251-52.45663.263
252-28.72283.404
253-113.4939.834
254-75.81651.991
255116.6883.998
25669.76226.479
25745.21991.619
258-36.6122.9218
2595.6153-29.401
260126.913.051
261-67.275-15.982
262154.96-54.03
26373.417-40.791
264-65.74956.437
265-152.2469.388
26656.987-23.617
267-61.843-79.317
26848.6551.5849
269-98.334-60.469
27081.657-28.603
27188.51227.962
2729.9698-8.5504
273-19.241-12.356
27424.878-28.886
275119.61-39.782
27620.981-5.0984
2773.4788-81.163
278-17.814-9.7976
279283.9125.53
280-10.929-24.001
281-83.57520.499
28260.242-68.956
2837.037126.173
28450.089-107.51
285-70.738-11.659
286-80.30162.717
28739.325-10.976
28825.674-14.406
289156.91-39.442
29063.791-17.454
291-13.679-48.784
29299.848-51.238
293147.457.554
294-10.643-32.351
295123.8-221.94
29660.7341.0906
29793.16626.073
298208.34-81.103
2999.4664-15.228
30084.079-13.084
301-4.1917-21.146
30221.727-71.332
30370.753-69.581
304-21.731-15.243
305300.13-3.9141
306-54.496-49.373
307156.24-12.934
308-115.26-9.8431
30942.24114.735
3106.200930.873
31198.89242.379
31283.08558.391
313-111.58-59.78
314-71.791-38.594
31577.377-98.348
31647.308-56.425
31712.37360.55
31819.715-72.505
31942.083-22.871
320-42.419-64.243
321-92.751-87.276
322-235.39-107.96
323-54.181-75.971
32488.06728.055
325-69.4888.145
32663.4956.844
32739.35927.073
328-21.587-2.255
32913.03-32.988
330102.68-31.405
33161.13532.551
332-109.0996.3
33323.713-48.541
334-24.59510.649
335152.6111.507
336182.73-41.612
337-26.252-23.214
33814.458-39.765
33926.142-19.703
34029.15-27.15
341228.04-1.112
3429.123-2.4674
343206.56-50.786
344144.31-39.252
345-76.474-15.826
346-58.097-56.15
347-58.415-55.432
348-13.078-84.39
349-32.846-50.604
35067.47914.925
351-99.651-78.255
3528.095813.62
35330.423-26.222
354-74.467-5.9409
35566.397-105.69
3566.8828-16.194
357-2.3954-53.26
35859.663-14.524
359-111.94-55.443
360-11.43960.825
361-35.787-28.261
362149.48-99.557
36353.74947.558
364-69.4835.4544
36513.503-53.331
366-6.3216-55.952
367-51.6764.4054
36822.11679.706
369200.9434.077
3709.05346.8888
371143.36-79.128
372102.56-38.836
373225.64-102.56
37429.502-73.437
375-72.90723.119
376-4.07336.87
377-68.36538.201
37841.034-43.656
37937.979-12.931
38015.819-2.6961
381-66.494-19.506
382-24.828-7.9049
38399.267-11.875
38458.79120.718
385-24.781-15.335
386-36.09612.07
38796.486-57.796
388-39.119-88.078
38914.398-62.282
390149.46-21.542
391126.99-3.9829
392-96.73649.773
393-125.14-55.326
39442.466-19.211
39534.498-39.112
396-2.7757-58.708
39727.564-81.506
398-91.882-21.157
39990.38249.618
400-2.0544-93.907
40175.519-27.932
40279.53317.753
403-6.2312-63.101
404131.010.19885
405120.7-149.83
40632.562-125.3
407-126.11-20.654
40837.759-100.13
409-87.95-68.632
41044.832-108.59
411123.75-61.179
41213.99-46.68
413-22.534-10.449
41487.279-48.746
415187.5515.713
416-4.3677-28.857
417-19.469-37.069
418-53.5625.668
4195.1122-5.1075
42061.189-17.225
42196.837-63.106
42246.681-2.1308
42352.958-21.333
42474.85912.971
425-66.465-35.642
426231.38-24.737
42743.769-13.298
42844.959-6.217
42948.895-101.88
430-46.667-17.471
43145.244-19.767
432-3.7646-23.204
433-70.42-86.316
43459.265-0.31501
4352.367126.821
436479.95145.03
43743.813-47.701
43899.23-53.515
43946.426-63.342
440142.51-62.542
441117.04-11.323
442-104.08-58.234
443-67.812-32.364
444-161.53-57.598
44517.909-71.608
446-20.13962.051
4471.6322-5.8761
448-40.141-14.779
449-127.76-33.205
450-42.756-61.405
451-116.6421.883
45293.926-34.325
453-57.443-8.2695
454-53.71134.682
455114.03-40.554
45672.478-19.876
457-43.827-14.705
458156.05-55.549
459-84.834-8.2972
460161.2225.755
461-2.1202-35.668
462-27.867-60.168
46353.18129.992
464188.762.4838
46524.513-77.043
466-70.33279.308
46739.03734.902
468-34.449-10.019
46925.689-119.43
470-116.75-46.016
47132.97431.687
472-130.291.494
473-83.861-60.095
474-105.84-33.098
475-21.907-50.235
476-39.992-5.1298
477-98.16-86.31
478-111.05-57.429
479-49.974-28.755
480-41.7238.8063
481-97.678-71.847
48263.496-12.003
483-48.449-18.31
484125.89-19.906
485110.4663.861
486-68.465-74.166
48794.74361.747
488139.18-56.256
489-98.0912.9159
4900.4005818.052
491-58.093-29.203
492-41.71543.177
493-59.263-20.36
49460.212-14.696
495-190.23-56.463
49628.4568.623
49765.169.8664
49851.935-62.796
49955.06734.521
500-36.405-8.3381
501-34.161-24.637
502-3.918-12.846
503-29.832-28.299
504-51.80450.576
505-111.03-23.291
506-27.496-67.83
507-75.727-69.333
50855.4955.4821
50955.00264.315
510-14.50721.044
511-63.278-24.8
512-118.13-2.4874
513-12.025-31.447
514123.491.6785
515-114.01-0.30208
51624.48127.057
517-6.4659-57.398
51817.72433.219
519162.9162.18
52074.998-30.47
521-44.276-72.068
52253.549-22.911
523-101.62-50.312
524-68.425-21.861
525-65.553-87.455
5269.5289-10.984
52762.965-23.231
52885.557-74.46
52981.5511.877
530-58.13344.329
531-102.62-26.716
53239.57844.544
5337.8543-25.754
534-64.827-87.085
535308.75-31.451
53619.699-32
537-121.23-27.569
538-75.53516.981
539124.3430.681
540-90.007-8.0157
541-130.6622.059
542-45.188-13.199
54393.968-31.411
54453.107-33.366
54593.837-59.63
54622.033-13.568
54720.949-92.554
548-91.444-35.817
54932.088-66.574
550-41.467-89.716
55129.36118.113
55211.29-66.187
553-6.546435.127
554-91.687-43.96
5550.52905-29.602
556138.05-66.786

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: 73.5% (cumulative 73.5%)1PC2: 19.4% (cumulative 93.0%)2PC3: 3.9% (cumulative 96.9%)3PC4: 0.9% (cumulative 97.8%)4PC5: 0.5% (cumulative 98.3%)5PC6: 0.3% (cumulative 98.6%)6PC7: 0.2% (cumulative 98.8%)7PC8: 0.1% (cumulative 99.0%)8PC9: 0.1% (cumulative 99.1%)9PC10: 0.1% (cumulative 99.2%)10cumulative explained variancePC variancecumulativeprincipal component · cumulative (dashed)
View explained variance values
Variance per displayed principal component
ComponentSpectral variance
PC173.54%
PC219.45%
PC33.90%
PC40.93%
PC50.49%
PC60.31%
PC70.20%
PC80.14%
PC90.13%
PC100.12%
X-Y spectral correlation 4

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 chloride_average

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

X_svc_hr1024i · chloride_average spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale

Spectral association with chloridometer_reading1

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

X_svc_hr1024i · chloridometer_reading1 spectral correlation-1-0.500.51absolute correlation envelopesigned correlationabsolute correlation01,0002,0003,000|r|signed raxis · Pearson correlation scale

Spectral association with chloridometer_reading2

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

X_svc_hr1024i · chloridometer_reading2 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
chloride_average0.2667070.08140.0%
chloridometer_reading10.2697060.08130.0%
chloridometer_reading20.2717060.08260.0%
chloridometer_reading30.2717060.0830.0%

Metric interpretation reference

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

Metric catalog 30

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

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

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

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

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

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

Curated scientific variables

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

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

VariableRoleDistinct valuesCompleteRange / balance
pot_numberM318100%1 – 324
trialM2100%IR 1.744
genotypeM23100%IR 6.429
salt_treatment_mm_naclM3100%0 – 75
instrument_nameM2100%IR 2.147
chloride_averageY300100%0 – 7945
chloridometer_reading1Y16099.75%0 – 281
chloridometer_reading2Y17099.75%0 – 283
chloridometer_reading3Y16999.75%0 – 282

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 4

chloride_average

target · numeric

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

chloride_average distribution01002003000 – 331.1: 251331.1 – 662.1: 76662.1 – 993.2: 54993.2 – 1324: 491324 – 1655: 381655 – 1986: 421986 – 2317: 452317 – 2648: 522648 – 2980: 362980 – 3311: 453311 – 3642: 293642 – 3973: 293973 – 4304: 174304 – 4635: 164635 – 4966: 154966 – 5297: 65297 – 5628: 95628 – 5959: 05959 – 6290: 06290 – 6621: 36621 – 6952: 06952 – 7283: 07283 – 7614: 07614 – 7945: 302,0004,0006,0008,000
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
1634 ± 1.53e+03
Median
?50th percentile: half the non-missing values lie at or below it.
1147
Range
?Smallest and largest recorded non-missing values.
0 – 7945
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.94
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.95 / 0.39
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

chloridometer_reading1

target · numeric

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

chloridometer_reading1 distribution01002003000 – 11.71: 24811.71 – 23.42: 7723.42 – 35.12: 5735.12 – 46.83: 4646.83 – 58.54: 4058.54 – 70.25: 4070.25 – 81.96: 4081.96 – 93.67: 5993.67 – 105.4: 38105.4 – 117.1: 43117.1 – 128.8: 25128.8 – 140.5: 32140.5 – 152.2: 16152.2 – 163.9: 16163.9 – 175.6: 13175.6 – 187.3: 6187.3 – 199: 11199 – 210.8: 0210.8 – 222.5: 0222.5 – 234.2: 3234.2 – 245.9: 0245.9 – 257.6: 0257.6 – 269.3: 0269.3 – 281: 30100200300
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 2
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
57.85 ± 54.2
Median
?50th percentile: half the non-missing values lie at or below it.
41
Range
?Smallest and largest recorded non-missing values.
0 – 281
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.936
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.95 / 0.41
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

chloridometer_reading2

target · numeric

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

chloridometer_reading2 distribution01002003000 – 11.79: 24211.79 – 23.58: 8723.58 – 35.38: 5235.38 – 47.17: 4747.17 – 58.96: 3858.96 – 70.75: 4470.75 – 82.54: 4882.54 – 94.33: 4794.33 – 106.1: 40106.1 – 117.9: 39117.9 – 129.7: 31129.7 – 141.5: 30141.5 – 153.3: 18153.3 – 165.1: 14165.1 – 176.9: 15176.9 – 188.7: 6188.7 – 200.5: 9200.5 – 212.2: 0212.2 – 224: 1224 – 235.8: 2235.8 – 247.6: 0247.6 – 259.4: 0259.4 – 271.2: 0271.2 – 283: 30100200300
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 2
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
58.18 ± 54.6
Median
?50th percentile: half the non-missing values lie at or below it.
41
Range
?Smallest and largest recorded non-missing values.
0 – 283
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.939
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.95 / 0.38
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

chloridometer_reading3

target · numeric

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

chloridometer_reading3 distribution01002003000 – 11.75: 24511.75 – 23.5: 8723.5 – 35.25: 4635.25 – 47: 5047 – 58.75: 3758.75 – 70.5: 4170.5 – 82.25: 4782.25 – 94: 4994 – 105.8: 40105.8 – 117.5: 44117.5 – 129.2: 29129.2 – 141: 27141 – 152.8: 19152.8 – 164.5: 16164.5 – 176.2: 13176.2 – 188: 6188 – 199.8: 11199.8 – 211.5: 0211.5 – 223.2: 0223.2 – 235: 3235 – 246.8: 0246.8 – 258.5: 0258.5 – 270.2: 0270.2 – 282: 30100200300
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 2
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
58.12 ± 54.4
Median
?50th percentile: half the non-missing values lie at or below it.
40
Range
?Smallest and largest recorded non-missing values.
0 – 282
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.937
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.94 / 0.36
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

Metadata 12

pot_number

metadata · numeric

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

pot_number distribution02040601 – 14.46: 4114.46 – 27.92: 3827.92 – 41.38: 4241.38 – 54.83: 3854.83 – 68.29: 4168.29 – 81.75: 3681.75 – 95.21: 4195.21 – 108.7: 34108.7 – 122.1: 40122.1 – 135.6: 39135.6 – 149: 41149 – 162.5: 37162.5 – 176: 36176 – 189.4: 41189.4 – 202.9: 38202.9 – 216.3: 40216.3 – 229.8: 33229.8 – 243.2: 39243.2 – 256.7: 38256.7 – 270.2: 34270.2 – 283.6: 10283.6 – 297.1: 12297.1 – 310.5: 13310.5 – 324: 130100200300400
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
143.1 ± 84.7
Median
?50th percentile: half the non-missing values lie at or below it.
142
Range
?Smallest and largest recorded non-missing values.
1 – 324
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.592
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.11 / -1
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

trial

metadata · categorical

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

trial classestrial01trial01: 518518trial02trial02: 297297
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 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.
0.95
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
2
Top class
?Most frequent recorded category and its observation count.
trial01 (518)

genotype

metadata · categorical

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

genotype classesNM11-081NM11-081: 4545NM11-072NM11-072: 4545LONGII9018LONGII9018: 4545NM11-085NM11-085: 4545AZ11-012BAZ11-012B: 4545DOAN9024DOAN9024: 4545NM11-084NM11-084: 4444NM11-062NM11-062: 4444BERL9031BERL9031: 4343BERL9043BERL9043: 4343+10 more+10 more: 344344
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Classes
?Number of distinct recorded category values.
23
Balance (entropy)
?Normalized Shannon entropy, from 0 for one dominant class to 1 for equal class frequencies.
0.97
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
6
Top class
?Most frequent recorded category and its observation count.
NM11-081 (45)

replicate

metadata · numeric

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

replicate distribution01002001 – 1.167: 1651.167 – 1.333: 01.333 – 1.5: 01.5 – 1.667: 01.667 – 1.833: 01.833 – 2: 02 – 2.167: 1612.167 – 2.333: 02.333 – 2.5: 02.5 – 2.667: 02.667 – 2.833: 02.833 – 3: 03 – 3.167: 1653.167 – 3.333: 03.333 – 3.5: 03.5 – 3.667: 03.667 – 3.833: 03.833 – 4: 04 – 4.167: 1654.167 – 4.333: 04.333 – 4.5: 04.5 – 4.667: 04.667 – 4.833: 04.833 – 5: 15912345
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
2.99 ± 1.41
Median
?50th percentile: half the non-missing values lie at or below it.
3
Range
?Smallest and largest recorded non-missing values.
1 – 5
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.472
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.0016 / -1.3
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

salt_treatment_mM_NaCl

metadata · numeric

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

salt_treatment_mM_NaCl distribution01002003000 – 3.125: 2633.125 – 6.25: 06.25 – 9.375: 09.375 – 12.5: 012.5 – 15.62: 015.62 – 18.75: 018.75 – 21.88: 021.88 – 25: 025 – 28.12: 028.12 – 31.25: 031.25 – 34.38: 034.38 – 37.5: 037.5 – 40.62: 040.62 – 43.75: 043.75 – 46.88: 046.88 – 50: 050 – 53.12: 27253.12 – 56.25: 056.25 – 59.38: 059.38 – 62.5: 062.5 – 65.62: 065.62 – 68.75: 068.75 – 71.88: 071.88 – 75: 280020406080
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
42.45 ± 31.1
Median
?50th percentile: half the non-missing values lie at or below it.
50
Range
?Smallest and largest recorded non-missing values.
0 – 75
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.732
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.42 / -1.5
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

instrument_name

metadata · categorical

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

instrument_name classesSVC HR-1024iSVC HR-1024i: 556556NIR-S-G1NIR-S-G1: 259259
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 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.
0.9
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
2
Top class
?Most frequent recorded category and its observation count.
SVC HR-1024i (556)

spectroscopy_type

metadata · categorical

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

spectroscopy_type classesVIS-NIRVIS-NIR: 556556NIRNIR: 259259
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 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.
0.9
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
2
Top class
?Most frequent recorded category and its observation count.
VIS-NIR (556)

axis_min

metadata · numeric

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

axis_min distribution0200400600339 – 362.4: 556362.4 – 385.8: 0385.8 – 409.2: 0409.2 – 432.7: 0432.7 – 456.1: 0456.1 – 479.5: 0479.5 – 502.9: 0502.9 – 526.3: 0526.3 – 549.8: 0549.8 – 573.2: 0573.2 – 596.6: 0596.6 – 620: 0620 – 643.4: 0643.4 – 666.8: 0666.8 – 690.2: 0690.2 – 713.7: 0713.7 – 737.1: 0737.1 – 760.5: 0760.5 – 783.9: 0783.9 – 807.3: 0807.3 – 830.8: 0830.8 – 854.2: 0854.2 – 877.6: 0877.6 – 901: 2591002005001,000
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
517.6 ± 262
Median
?50th percentile: half the non-missing values lie at or below it.
339
Range
?Smallest and largest recorded non-missing values.
339 – 901
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.506
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
0.78 / -1.4
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

axis_max

metadata · numeric

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

axis_max distribution02004006001,702 – 1736: 2591736 – 1770: 01770 – 1804: 01804 – 1838: 01838 – 1871: 01871 – 1905: 01905 – 1939: 01939 – 1,973: 01,973 – 2007: 02007 – 2041: 02041 – 2075: 02075 – 2108: 02108 – 2142: 02142 – 2176: 02176 – 2210: 02210 – 2,244: 02,244 – 2278: 02278 – 2312: 02312 – 2346: 02346 – 2380: 02380 – 2413: 02413 – 2447: 02447 – 2481: 02481 – 2,515: 5561,0002,0005,00010,000
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
2257 ± 379
Median
?50th percentile: half the non-missing values lie at or below it.
2,515
Range
?Smallest and largest recorded non-missing values.
1,702 – 2,515
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.168
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.78 / -1.4
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

n_points_original

metadata · numeric

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

n_points_original distribution0200400600228 – 261.1: 259261.1 – 294.2: 0294.2 – 327.4: 0327.4 – 360.5: 0360.5 – 393.6: 0393.6 – 426.8: 0426.8 – 459.9: 0459.9 – 493: 0493 – 526.1: 0526.1 – 559.2: 0559.2 – 592.4: 0592.4 – 625.5: 0625.5 – 658.6: 0658.6 – 691.8: 0691.8 – 724.9: 0724.9 – 758: 0758 – 791.1: 0791.1 – 824.2: 0824.2 – 857.4: 0857.4 – 890.5: 0890.5 – 923.6: 0923.6 – 956.8: 0956.8 – 989.9: 0989.9 – 1,023: 5562004006008001,0001,200
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 0
Mean ± SD
?Arithmetic mean and standard deviation in the variable's stated unit.
770.4 ± 370
Median
?50th percentile: half the non-missing values lie at or below it.
1,023
Range
?Smallest and largest recorded non-missing values.
228 – 1,023
CV
?Coefficient of variation: standard deviation divided by absolute mean; unstable when the mean is near zero.
0.481
Skew / kurtosis
?Distribution asymmetry and excess kurtosis. A Gaussian distribution has skewness 0 and excess kurtosis 0.
-0.78 / -1.4
Normal?
?Descriptive normality-test result. A non-normal target is not automatically a defective variable.
no

decoder

metadata · categorical

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

decoder classespandas.read_csv, numpy.interppandas.read_csv, numpy.interp: 556556pandas.read_csvpandas.read_csv: 259259
n / missing
?Recorded observation count and number of missing values for this variable.
815 / 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.
0.9
Imbalance ratio
?Largest class count divided by smallest class count; 1 indicates equal counts.
2
Top class
?Most frequent recorded category and its observation count.
pandas.read_csv, numpy.interp (556)

scan_id

metadata · categorical

Compare recorded category counts and class balance. No distribution plot is available; use the recorded statistics below.

n / missing
?Recorded observation count and number of missing values for this variable.
815 / 259
Classes
?Number of distinct recorded category values.
556
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.
HR.060623.0000.sig (1)
Constant metadata 8

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

  • article_urlhttps://acsess.onlinelibrary.wiley.com/doi/10.1002/ppj2.70012
  • doi_publication10.1002/ppj2.70012
  • signal_typereflectance
  • axis_unitnm
  • licenseNOASSERTION
  • rights_statusno_explicit_repository_license
  • public_release_allowedFalse
  • n_points_interpolated2177

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
Samples556
Observations (total)815
Exported observations per unitmin 1 · mean 1 · max 1
Identity statusavailable
Documented technical repetitionsND
Source unitOne spectrum exported per plant/pot in each trial

Splits

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

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

Load this dataset

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

# pip install nirs4all-datasets
from nirs4all_datasets import get

# Hosted canonical access requires a configured Dataverse DOI and token
ds = get("github_grapevine_chloride_nir", token="…")
X, y = ds.x(), ds.y()
print(X.shape, y.shape)

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