Influence of Linpro and dietary copper on feedlot cattle performance, carcass characteristics, and fatty acid composition of beef
Bibliographic record
Abstract
Human diets often contain high levels of saturated fatty acids that can have deleterious health consequences such as obesity, diabetes, and heart disease. In contrast, omega-3 fatty acids, which are essential for human nutrition, are consumed at relatively low levels despite of their positive effects on health. Natural sources of omega-3 fatty acids include fresh legumes, cool-season grasses, flaxseed, and fish oil. In spite of the fact that fresh forages often are a key part of the cattle diet, beef is a relatively poor source of omega-3 fatty acids because of biohydrogenation, the action of microorganisms in the rumen that convert polyunsaturated fatty acids, including the omega-3 fats, into saturated fats. Previous research at Kansas State University has shown that feeding cattle flax-based feeds can increase concentrations of omega-3 fatty acids in beef. Researchers at Colorado State University have reported that elevated levels of dietary copper can inhibit the biohydrogenation process to yield beef with greater proportions of polyunsaturated fatty acids. Our objective was to evaluate whether feeding elevated copper concentrations in conjunction with Linpro (O&T Farms; Regina, Saskatchewan, Canada), a co-extruded blend of field peas and flaxseed, could be used to further improve the levels of omega-3 fatty acids in beef.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".