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Record W2022138702 · doi:10.1007/s11745-007-3044-6

Rapid Analysis of Acylglycerols in Low Molecular Weight Milk Fat Fractions

2007· article· en· W2022138702 on OpenAlexafffund
R. John Craven, Robert W. Lencki

Bibliographic record

VenueLipids · 2007
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsUniversity of Guelph
FundersMinistry of Food and Drug SafetyOntario Ministry of Agriculture, Food and Rural AffairsDairy Farmers of Ontario
KeywordsGlycerideLipidologyClinical chemistryChemistryChromatographyFood scienceDiglycerideBiochemistryFatty acid

Abstract

fetched live from OpenAlex

A suitable analytical method was required to facilitate development of an industrial-scale short-path distillation (SPD) process. Short-path distillation produces milk fat distillates (MFD) enriched in low molecular weight milk fat components-viz. free fatty acids, monoacylglycerols, diacylglycerols, cholesterol and low molecular weight triacylglycerols. In this case, solid-phase extraction (SPE) was considered a better alternative than thin-layer chromatography for separating polar and apolar lipid components in MFD samples due to its speed and near-complete recoveries. Solid-phase extraction of MFDs yielded two fractions, both of which are sufficiently pure for subsequent analysis by gas chromatography. This procedure provided rapid and complete chemical characterization (including mass balances) of low-molecular weight milk-fat fractions.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.007
GPT teacher head0.243
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2007
Admission routes2
Has abstractyes

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