Dietary flaxseed: what we know and don’t know about its effects on cardiovascular disease
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".