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Long-chain omega-3 fatty acids eicosapentaenoic acid and docosahexaenoic acid dose-dependently reduce fasting serum triglycerides

2010· review· en· W2170485201 on OpenAlex
Kathy Musa‐Veloso, Malcolm A. Binns, Alexandra Catherine Kocenas, Theresa Poon, Julie Ann Elliot, Harry B. Rice, Hilde Oppedal-Olsen, Hilary Lloyd, Shawna L. Lemke

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

VenueNutrition Reviews · 2010
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of TorontoCantox Health Sciences International
FundersCargill
KeywordsEicosapentaenoic acidDocosahexaenoic acidInternal medicineEndocrinologyFatty acidMedicinePlaceboChemistryPolyunsaturated fatty acidBiochemistry

Abstract

fetched live from OpenAlex

The objectives of this review were to determine whether the long-chain omega-3 fatty acids eicosapentaenoic acid and/or docosahexaenoic acid dose-dependently reduce fasting serum triglycerides (TG) and, if so, to create a mathematical model that may be used to predict potential percent reductions in fasting serum TG levels at the recommended intakes of 200-500 mg/day. The assessment included 15 randomized controlled trials that met pre-defined inclusion and exclusion criteria. Across these 15 studies, the dose-response was modeled using a first-order elimination curve. The response variable was defined as percent change from baseline in fasting serum TG, adjusted for the placebo effect. A weighting factor equal to the product of each study's sample size and quality score was used. Using the equation of the dose-response curve, predicted reductions in fasting serum TG levels at the recommended long-chain omega-3 fatty acid intakes of 200-500 mg/day are 3.1 to 7.2%.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.934
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0060.002
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0010.001

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 head0.082
GPT teacher head0.383
Teacher spread0.300 · 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