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Record W2168330912 · doi:10.1002/lite.200800081

Confusion over different types of <i>n</i>‐3 polyunsaturated fatty acids

2009· article· en· W2168330912 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLipid Technology · 2009
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsTrinity College
Fundersnot available
KeywordsPolyunsaturated fatty acidDocosahexaenoic acidEicosapentaenoic acidConfusionLong chainFood scienceChemistryalpha-Linolenic acidLinolenic acidBiochemistryFatty acidLinoleic acid

Abstract

fetched live from OpenAlex

Abstract There are two kinds of n‐3 polyunsaturated fatty acid (PUFA). Alpha‐linolenic acid (ALA) is the parent n‐3 PUFA; it cannot be synthesized by the human body and as a result is an essential fatty acid. The two long chain n‐3 PUFA eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) can in principle be synthesized from ALA or obtained from the diet. While the cardioprotective effects of long chain n‐3 PUFA are well established the effects of ALA on the cardiovascular system are more controversial. The Lyon Diet Heart Study which it is claimed provides evidence for beneficial effects of ALA on the cardiovascular system is flawed. The argument that ALA conversion into EPA and DHA provides significant quantities of the two long chain n‐3 PUFA is unsustainable as rates of conversion are too low. To avoid confusion a distinction needs to be drawn between ALA and the long chain n‐3 PUFA. Health claims for foods rich in EPA and DHA cannot be extended to foods rich in ALA nor is ALA a substitute for EPA and DHA in vegetarian diets.

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.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.289
Teacher spread0.277 · 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