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Record W2067631691 · doi:10.5539/gjhs.v4n3p72

Seafood Consumption and Components for Health

2012· review· en· W2067631691 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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueGlobal Journal of Health Science · 2012
Typereview
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental healthConsumption (sociology)Eicosapentaenoic acidHealth benefitsPolyunsaturated fatty acidDiseaseNutrientHealth promotionFood scienceMedicinePublic healthBiologyFatty acidTraditional medicineBiochemistryEcologyInternal medicine

Abstract

fetched live from OpenAlex

In recent years, in developed countries and around the world, lifestyle-related diseases have become a serious problem. Numerous epidemiological studies and clinical trials have demonstrated that diet is one of the major factors that influences susceptibility to lifestyle-related diseases, especially the middle-senile state. Studies examining dietary habits have revealed the health benefits of seafood consumption. Seafood contains functional components that are not present in terrestrial organisms. These components include n-3-polyunsaturated fatty acids, such as eicosapentaenoic acid and docosahexsaenoic acid, which aid in the prevention of arteriosclerotic and thrombotic disease. In addition, seafood is a superior source of various nutrients, such as protein, amino acids, fiber, vitamins, and minerals. This review focuses on the components derived from seafood and examines the significant role they play in the maintenance and promotion of health.

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)0.009
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.878

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.238
GPT teacher head0.506
Teacher spread0.268 · 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