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Record W2316961648 · doi:10.3109/09637486.2016.1161012

Fat composition of vegetable oil spreads and margarines in the USA in 2013: a national marketplace analysis

2016· article· en· W2316961648 on OpenAlexaff
Marcella Garsetti, Douglas A. Balentine, Peter L. Zock, W. Blom, Anne J. Wanders

Bibliographic record

VenueInternational Journal of Food Sciences and Nutrition · 2016
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUnilever (Canada)
Fundersnot available
KeywordsComposition (language)Food scienceTotal fatIngredientLinoleic acidChemistryLinolenic acidTrans fatSaturated fatFatty acidCholesterolBiochemistry

Abstract

fetched live from OpenAlex

Worldwide, the fat composition of spreads and margarines ("spreads") has significantly changed over the past decades. Data on fat composition of US spreads are limited and outdated. This paper compares the fat composition of spreads sold in 2013 to that sold in 2002 in the USA. The fat composition of 37 spreads representing >80% of the US market sales volume was determined by standard analytical methods. Sales volume weighted averages were calculated. In 2013, a 14 g serving of spread contained on average 7.1 g fat and 0.2 g trans-fatty acids and provided 22% and 15% of the daily amounts recommended for male adults in North America of omega-3 α-linolenic acid and omega-6 linoleic acid, respectively. Our analysis of the ingredient list on the food label showed that 86% of spreads did not contain partially hydrogenated vegetable oils (PHVO) in 2013. From 2002 to 2013, based on a 14 g serving, total fat and trans-fatty acid content of spreads decreased on average by 2.2 g and 1.5 g, respectively. In the same period, the overall fat composition improved as reflected by a decrease of solid fat (from 39% to 30% of total-fatty acids), and an increase of unsaturated fat (from 61% to 70% of total-fatty acids). The majority of US spreads no longer contains PHVO and can contribute to meeting dietary recommendations by providing unsaturated fat.

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 score0.130
Threshold uncertainty score0.110

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.033
GPT teacher head0.339
Teacher spread0.306 · 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

Citations29
Published2016
Admission routes1
Has abstractyes

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