Review: Trans-forming beef to provide healthier fatty acid profiles
Bibliographic record
Abstract
Dugan, M. E. R., Aldai, N., Aalhus, J. L., Rolland, D. C. and Kramer, J. K. G. 2011. Review:rans-forming beef to provide healthier fatty acid profiles. Can. J. Anim. Sci. 91: 545-556.Trans fatty acids are found naturally in foods, particularly in those derived from ruminant animals, such as beef and dairy cattle. Over the past few decades, human consumption of trans fatty acids has increased, but this has been mainly from products containing partially hydrogenated vegetable oils. The correlation of trans fatty acid consumption with diseases such as coronary heart disease has been cause for concern, and led to recommendations to reduce their consumption. Trans fatty acids, however, have differing effects on human health. Therefore, in foods produced from ruminant animals, it is important to know their trans fatty acid composition, and how to enrich or deplete fatty acids that have positive or negative health effects. This review will cover the analysis of trans fatty acids in beef, their origin, how to manipulate their concentrations, and give a brief overview of their health effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".