Live growth performance, carcass grading characteristics, and harvest yields of beef steers supplemented zilpaterol hydrochloride and offered ad libitum or maintenance energy intake
Bibliographic record
Abstract
A trial was conducted to examine live growth efficiency, harvest yields, and carcass grading performance of steers fed at maintenance (M) or at ad libitum (A) level of intake during zilpaterol hydrochloride (Z) supplementation. Single-sired, beef steers (n = 56; start of trial BW 590 ± 36 kg) blocked (n = 2) by weight and terminal implant were sorted into pairs (n = 14 per block) by weight. Pairs of steers were initially assigned to 0, 28, or 56 d of feeding. Within 28 or 56 d, pairs were assigned to M or A intake. Steers within a pair assigned to 56 d of feeding were randomly assigned to either 20 d of Z supplementation (90 mg/d per steer) with a 4 d withdrawal period prior to slaughter or to no ZH supplementation (C). Steers were housed and fed in individual pens. Weights of all non-carcass and carcass components were recorded at slaughter; carcasses were graded 24-h postmortem. Data were analyzed via a mixed model; the fixed effect was treatment combination with random effects of block and pair. Live growth data used harvest day as the repeated measure and animal as the subject. Single df contrasts were constructed for day 0 vs. day 28, day 0 vs. day 56, day 28 vs. day 56, M vs. A, and C vs. Z. Treatment impacted (P ≤ 0.05) live ADG; contrasts indicated A (1.33) was greater than M (0.14 kg), and Z (1.12) was greater than C (0.82 kg). Similarly, carcass ADG differences (P < 0.01) indicated A (1.04) was greater than M (0.36 kg), and Z (1.35) was greater than C (0.71 kg). Intake level altered BW and empty body weight (EBW); M cattle had reduced BW and EBW (P < 0.01, 585 and 540 kg) than A cattle (647 and 597 kg). Cattle fed at M had less carcass and internal cavity mass (P < 0.01, 359 and 79.4 kg) than A cattle (394 and 93.5 kg). Liver mass was reduced by M feeding (P < 0.01; M-5.03, A-6.69 kg) and Z treatment (P < 0.01; Z-5.64, C-6.06 kg). Moreover, mass of total splanchnic tissue was less (P < 0.01) for M cattle than A cattle (59.8 vs. 72.5 kg). Dressed carcass yield was greater (P < 0.01) for Z than C cattle (63.5 vs. 61.6%). Cattle fed at M had less 12th rib s.c. fat, lower numerical U.S. yield grades (P < 0.01; M-1.71 cm and 3.3, A-2.46 cm and 4.3) and lower numerical Canadian yield grades (P < 0.01; 51.9 vs. 53.9% for M and A, respectively) than A cattle. Results indicate that energy intake level and Z supplementation influence live and carcass growth, carcass transfer, kill yields, and carcass characteristics across time.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".