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Record W2165950102 · doi:10.7205/milmed-d-14-00147

Omega-3 Fatty Acid Biochemistry: Perspectives from Human Nutrition

2014· review· en· W2165950102 on OpenAlexafffund
Sheila M. Innis

Bibliographic record

VenueMilitary Medicine · 2014
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsChild and Family Research Institute
FundersCanadian Institutes of Health Research
KeywordsDocosahexaenoic acidEicosapentaenoic acidPolyunsaturated fatty acidLinoleic acidMetabolismFatty acidBiochemistryOmega 3 fatty acidChemistryBiology

Abstract

fetched live from OpenAlex

The possibility that western diets poor in omega-3 and rich in omega-6 fatty acids contribute to the increasing burden of chronic diseases including neurological problems is becoming recognized. Modern, westernized diets provide 80 to 90% of polyunsaturated fatty acids as omega-6 linoleic acid (LA) and are depleted in omega-3 fatty acids, giving a distorted balance of LA to α-linoleic acid, and to eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). LA intakes exceed Δ-6 desaturase needs for maximal activity. LA accumulates in blood and tissue lipids with increasing intake, and this exacerbates competition between LA and limited omega-3 fatty acids for metabolism and acylation into tissue lipids. Increasing EPA and DHA intake decreases tissue omega-6 fatty acids while also providing EPA and DHA. However, strategies for EPA and DHA supplementation do not address potential underlying problems of omega-6 and omega-3 fatty acid imbalance in the food supply.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.004
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.002
Research integrity0.0020.003
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 head0.055
GPT teacher head0.390
Teacher spread0.335 · 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

Citations44
Published2014
Admission routes2
Has abstractyes

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