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Record W2102313297 · doi:10.1017/s1368980008003868

A comparison of the fat composition and prices of margarines between 2002 and 2006, when new Canadian labelling regulations came into effect

2008· article· en· W2102313297 on OpenAlexaffabout
Laurie Ricciuto, Kevin Lin, Valerie Tarasuk

Bibliographic record

VenuePublic Health Nutrition · 2008
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLabellingComposition (language)PopulationFood scienceChemistryMedicineArtBiochemistry

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the effect of the new Canadian labelling regulations on the fat composition and prices of margarines. STUDY DESIGN: A survey of all margarines sold in major supermarkets in the Greater Toronto area was conducted in 2006, and results were compared with those of a similar survey conducted in 2002. Average fat composition, proportion of 'trans fat-free' margarines and average prices of margarines were compared. A general linear model procedure was used to compare the relationship between price and fat composition in 2002 and 2006. RESULTS: Average amounts of trans fatty acids (TFA) and MUFA decreased, while average amounts of PUFA increased significantly from 2002 to 2006. The proportion of margarines with less than 0.2 g TFA/10 g serving rose significantly from 31 % in 2002 to 69 % in 2006. Margarines lower in TFA on average cost significantly more than margarines with greater amounts of these fats, and this relationship appeared stronger in 2006 relative to 2002. CONCLUSIONS: There is evidence of reductions in TFA in margarines since new labelling regulations came into effect in Canada; however, TFA reductions appeared to be restricted to higher-priced margarines. Results suggest that voluntary approaches (i.e. manufacturer incentives via labelling) to reduce population intakes of TFA will yield little changes in TFA content of low-cost products and thus may have limited benefit for lower-income groups, who are at higher risk of heart disease.

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 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.931

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.065
GPT teacher head0.348
Teacher spread0.283 · 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 teacher head, 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

Citations49
Published2008
Admission routes2
Has abstractyes

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