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Record W2903774087 · doi:10.1139/cjpp-2018-0547

Dietary flaxseed: what we know and don’t know about its effects on cardiovascular disease

2018· review· en· W2903774087 on OpenAlexafffundvenue
Mihir Parikh, Grant N. Pierce

Bibliographic record

VenueCanadian Journal of Physiology and Pharmacology · 2018
Typereview
Languageen
FieldMedicine
TopicPhytoestrogen effects and research
Canadian institutionsUniversity of ManitobaSt. Boniface Hospital
FundersCanadian Institutes of Health Research
KeywordsDiseaseMedicineFood scienceIntensive care medicineChemistryInternal medicine

Abstract

fetched live from OpenAlex

Flaxseed (Linum usitatissimum) is composed of a unique combination of bioactive components that appear to generate, through either an isolated or a synergistic action, a significant beneficial effect on the cardiovascular system. With a significant increase in the generation of data on the dietary impact of flaxseed on the cardiovascular system, a review of where we stand - what we know and what we still need to understand about these effects on the heart and the vasculature - was thought to be of value and the rationale for this paper. For example, although we now know how to deliver the bioactives most efficiently (oil versus ground seed versus whole seed), we do not know how different foods can influence that delivery. Further, we know flaxseed has anti-arrhythmic, anti-atherogenic, anti-hypertensive, and cholesterol-lowering actions in animal studies and some selected human trials but much more needs to be learned, particularly in human trials. These results have justified further commitment of resources to the initiation of human trials. Because of the impact of nutrition on many chronic diseases, this may not only be true for the effects of flaxseed on cardiovascular disease but may be just as relevant for many other disease conditions.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.034
GPT teacher head0.346
Teacher spread0.313 · 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 teacher head, not a consensus.

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

Citations46
Published2018
Admission routes3
Has abstractyes

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