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Record W1508616892 · doi:10.1002/0471142913.faa0103s00

Application of Low‐Resolution NMR for Simultaneous Moisture and Oil Determination in Food (Oilseeds)

2001· article· en· W1508616892 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.

Bibliographic record

VenueCurrent Protocols in Food Analytical Chemistry · 2001
Typearticle
Languageen
FieldPhysics and Astronomy
TopicNMR spectroscopy and applications
Canadian institutionsBruker (Canada)
Fundersnot available
KeywordsMoistureResolution (logic)ChemistryLow resolutionEnvironmental scienceHigh resolutionRemote sensingComputer scienceOrganic chemistryGeographyArtificial intelligence

Abstract

fetched live from OpenAlex

Basic principles of low-resolution NMR with an emphasis on the minispec for oil and moisture determinations. Pulsed NMR for moisture determination of wheat grains over the 8% to 15% moisture range. Minispec for rapid water and fat content over large temperature range without weighing or measuring temperature of samples. Moisture and oil determination by NMR with respect to bulk/packing density or sample weight. Basic NMR theory for water determination with example of on-line process control. FID and spin-echo applications to moisture in wheat, corn, soybeans, peanuts, and pecans.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.689
Threshold uncertainty score0.624

Codex and Gemma teacher scores by category

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

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 head0.019
GPT teacher head0.367
Teacher spread0.348 · 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