Effect of trenbolone acetate, melengestrol acetate, and ractopamine hydrochloride on the growth performance of beef cattle
Bibliographic record
Abstract
The effect of trenbolone acetate + estradiol (TBA) implants, melengestrol acetate (MGA), and ractopamine hydrochloride + TBA (RAC + TBA) on growth performance and carcass characteristics in beef cattle (n = 680; 279 ± 10.1 kg) fed barley grain/corn silage was examined in a 4 yr study (four pens per treatment per year; 262 ± 8 d feeding period). In the first 2 yr, treatments were (1) control heifers (H-CON; no growth promoters), (2) TBA-implanted heifers (H-TBA), (3) MGA heifers (H-MGA), (4) control steers (S-CON; no growth promoters), and (5) TBA-implanted steers (S-TBA). A sixth treatment (6) RAC + TBA steers (RAC + TBA) was included in years 3 and 4. Overall dry matter intake (DMI) of heifers was increased (P < 0.001) by TBA but not MGA. Compared with H-CONs, H-TBA had greater average daily gain (ADG) (P < 0.001), gain to feed ratio (G/F) (P < 0.001), and carcass weight (P < 0.001), whereas S-TBA had increased ADG (P < 0.001), G/F (P< 0.001), and carcass weight (P < 0.001) compared with S-CON. Compared with H-CON, H-MGA had increased (P < 0.01) ADG, G/F, and carcass weight. The RAC + TBA had increased (P < 0.01) ADG and carcass weight (3.2%) but not G/F or DMI compared with S-TBA. This 4 yr study showed a consistent positive impact of growth-enhancing technologies on the performance of Canadian feedlot cattle.
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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".