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Record W2945878060 · doi:10.3390/nu11051171

Dietary Flaxseed as a Strategy for Improving Human Health

2019· review· en· W2945878060 on OpenAlexafffund
Mihir Parikh, Thane G. Maddaford, J. Alejandro Austria, Michel Aliani, Thomas Netticadan, Grant N. Pierce

Bibliographic record

VenueNutrients · 2019
Typereview
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of ManitobaSt. Boniface Hospital
FundersCanadian Institutes of Health Research
KeywordsHealth benefitsLignanCardiovascular healthNutraceuticalDiseasealpha-Linolenic acidFunctional foodMedicineFood scienceBiochemistryBiotechnologyPharmacologyChemistryFatty acidBiologyTraditional medicinePolyunsaturated fatty acidDocosahexaenoic acidInternal medicineBotany

Abstract

fetched live from OpenAlex

Flaxseed is a rich source of the omega-3 fatty acid, alpha linolenic acid, the lignan secoisolariciresinol diglucoside and fiber. These compounds provide bioactivity of value to the health of animals and humans through their anti-inflammatory action, anti-oxidative capacity and lipid modulating properties. The characteristics of ingesting flaxseed or its bioactive components are discussed in this article. The benefits of administering flaxseed or the individual bioactive components on health and disease are also discussed in this review. Specifically, the current evidence on the benefits or limitations of dietary flaxseed in a variety of cardiovascular diseases, cancer, gastro-intestinal health and brain development and function, as well as hormonal status in menopausal women, are comprehensive topics for discussion.

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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.210
GPT teacher head0.495
Teacher spread0.285 · 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

Citations265
Published2019
Admission routes2
Has abstractyes

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