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Record W2015919431 · doi:10.1007/s11746-000-0167-5

<i>Trans</i> determination of edible oils by fourier transform near‐infrared spectroscopy

2000· article· en· W2015919431 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2000
Typearticle
Languageen
FieldChemistry
TopicSpectroscopy and Chemometric Analyses
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Food and Drug Administration
KeywordsCalibrationAnalytical Chemistry (journal)Fourier transform infrared spectroscopyChemistryPartial least squares regressionChemometricsAttenuated total reflectionSpectroscopyReproducibilityNear-infrared spectroscopyInfrared spectroscopyChromatographyMathematicsStatisticsOpticsOrganic chemistryPhysics

Abstract

fetched live from OpenAlex

Abstract A generalized partial‐least‐squares calibration for determination of the trans content of edible fats and oils by Fourier transform near‐infrared (FT‐NIR) spectroscopy using 8‐mm disposable glass vials for sample handling and measurement was developed. The trans contents of a broad range of oils were determined using the American Oil Chemists' Society single‐bounce horizontal attenuated total reflectance (SB‐HATR) mid‐infrared spectroscopic procedure, these trans reference data were used in the development of the generalized FT‐NIR calibration. Additional refined and product‐specific calibrations were also developed, and all the calibrations were assessed for their predictive capabilities using two sets of validation samples, one comprising a broad range of oil types and the other restricted to oils with specific characteristics. The FT‐NIR trans predictions obtained using the generalized calibration were in good agreement with the SB‐HATR results; the values were accurate and reproducible to within ±1.1 and ±0.5% trans , respectively, compared to a reproducibility of ±0.40% trans obtained for the SB‐HATR method. The accuracy of the predictions obtained from the generalized FT‐NIR calibration for particular oil types was not significantly improved by supplementing the base training set with samples of these specific types. Calibrating only these oil types did, however, produce a substantial improvement in predictive accuracy, aproaching that of the SB‐HATR method. These product specific calibrations produced serious predictive errors when nonrepresentative samples were analyzed. The incorporation of a supplementary discriminate analysis routine was found to be a powerful safeguard in flagging nonrepresentative samples as outliers and could also be used to select the calibration most appropriate for the characteristics of the sample being analyzed. Overall, it was concluded that FT‐NIR spectroscopy provides a viable alternative to the SB‐HATR/mid‐Fourier transform infrared method for trans determination, making use of more industrially robust instrumentation and equipped with a simpler sample handling system.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.248
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it