Review: Trans-forming beef to provide healthier fatty acid profiles
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.
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.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it