Subcutaneous fatty acid composition of steers finished as weanlings or yearlings with and without growth promotants
Bibliographic record
Abstract
BACKGROUND: The current study evaluated the subcutaneous fatty acid (FA) composition of calf- and yearling-fed steers with or without growth promoting implants. Crossbred steers (n = 112; 267 ± 5.0 kg) of the same contemporary group were allocated to one of four production system and implant strategy based treatments in a completely randomized design with a 2 × 2 factorial arrangement of treatments. RESULTS: There were no interactions (P > 0.05) between production systems and growth promoting implants for the total and individual subcutaneous FA. Yearling as opposed to calf finishing reduced (P < 0.05) subcutaneous proportions of C20:3n-6, trans (t)12-18:1, C14:0, several minor cis-monounsaturated FA (c-MUFA; c9-14:1, c11-16:1, c11-18:1, c12-18:1, c13-18:1, c9-20:1 and c11-20:1), and increased (P < 0 .05) subcutaneous proportions of t11c15-18:2, total and individual branched-chain FA. Subcutaneous fat from steers implanted with growth promotants had higher (P < 0.05) proportions of total polyunsaturated FA (PUFA), total n-6 PUFA, C18:2n-6 and individual t-18:1 isomers (t6 to t10) compared to non-implanted steers. CONCLUSIONS: Overall, current findings show that production systems and growth promotants led to only minor differences in subcutaneous FA composition of beef steers.
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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".