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Record W1969849845 · doi:10.1002/mnfr.201100700

Trans fat involvement in cardiovascular disease

2012· review· en· W1969849845 on OpenAlexafffund
Riya Ganguly, Grant N. Pierce

Bibliographic record

VenueMolecular Nutrition & Food Research · 2012
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersCanadian Institutes of Health Research
KeywordsDiseaseEpidemiologyMedicineCoronary heart diseaseCardiovascular healthBioinformaticsBiologyInternal medicine

Abstract

fetched live from OpenAlex

Coronary heart disease is becoming a worldwide epidemic and diet and lifestyle are well known contributing factors. Identifying the kinds of foods that may have a cardioprotective or cardiotoxic effect and understanding their molecular mechanisms of action has become of increasing importance. Through largely epidemiological evidence, trans fatty acid (TFA) intake has been associated with a variety of cardiovascular complications including atherosclerosis. Traditionally, industrial TFAs (iTFAs) have been associated with these deleterious cardiovascular effects. However, there is a current body of research that suggests that ruminant trans fats (rTFAs) may have a cardioprotective role within the heart. The molecular mechanisms whereby TFAs are delivering their effects are largely unknown. In the following review, we discuss recent in vitro, animal and epidemiological research to better understand the effect of TFAs in the diet on cardiovascular disease, particularly atherosclerosis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.203
GPT teacher head0.420
Teacher spread0.218 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations54
Published2012
Admission routes2
Has abstractyes

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