Changes in the fatty acid composition of steer subcutaneous fat, including biohydrogenation products, are minimal when finished on combinations of corn and barley grains and silages
Bibliographic record
Abstract
Corn production in Western Canada has increased with development of short-season varieties partially offsetting the use of barley as a silage and grain source. The current study evaluated effects of silage and cereal-grain source on subcutaneous fat (SCF) composition of finishing cattle. Steers (465 ± 28.0 kg) were assigned to 24 pens (12 steers per pen) in a 2 × 3 factorial design for an 89 d finishing study. Diets contained corn silage or barley silage at 8% [dry matter (DM)] combined either dry-rolled barley grain (BG; 86% of DM), corn grain (CG; 85% of DM), or an equal blend of BG and CG (85% of DM). Bone-in ribeyes were collected from four steers per pen, and subcutaneous fatty acids were analyzed by gas chromatography. Feeding dry-rolled CG increased dietary fat and 18:2n-6 concentrations, resulting in small increases in 18:2n-6, total n-6 fatty acids, and n-6/n-3 ratios in SCF (P < 0.05). There were no changes in proportions of major trans-18:1 isomers (t10-18:1 or t11-18:1), the main natural isomer of conjugated linoleic acid (cis9,t11–18:2), or n-3 fatty acids. Substitution of dry-rolled CG for BG in finisher diets can, therefore, be done without substantially altering the fatty acid composition of beef fat, including polyunsaturated fatty acid biohydrogenation products.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".