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Record W2079881092 · doi:10.1021/jf300585s

Profile of <i>trans</i> Fatty Acids (FAs) Including <i>Trans</i> Polyunsaturated FAs in Representative Fast Food Samples

2012· article· en· W2079881092 on OpenAlexaff
Cynthia Tyburczy, Pierluigi Delmonte, Ali Reza Fardin‐Kia, Magdi M. Mossoba, John K. G. Kramer, Jeanne I. Rader

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2012
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsTrans fatChemistryPolyunsaturated fatty acidChromatographyCis–trans isomerismGas chromatographyFood scienceSaturated fatFatty acidOrganic chemistryBiochemistryCholesterol

Abstract

fetched live from OpenAlex

The content of trans fat in foods is most commonly determined by summing the levels of individual trans fatty acids (FAs), analyzed as FA methyl esters (FAME) by gas chromatography. Current Official Methods of the American Oil Chemists' Society (AOCS) enable quantitation of total trans fat in foods but were not designed for the determination of transFA isomeric compositions. In the present study, the content of trans fat in 32 representative fast food samples ranged from 0.1 to 3.1 g per serving, as determined according to AOCS Official Method Ce 1j-07. Further analysis of FAME using the 200 m SLB-IL111 ionic liquid column yielded quantitative results of total, trans, saturated, and cis unsaturated fat that were comparable to those of Method Ce 1j-07 and also allowed for the complementary determination of individual trans 18:1, trans 18:2, and trans 18:3 FA isomeric compositions under conditions suitable for routine sample analysis.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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

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 head0.036
GPT teacher head0.290
Teacher spread0.254 · 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 designObservational
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

Citations45
Published2012
Admission routes1
Has abstractyes

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