Effect of rest, post-rest transport duration, and conditioning on performance, behavioural, and physiological welfare indicators of beef calves
Bibliographic record
Abstract
The aim of this study was to assess the effects of conditioning, rest, and post-rest transport duration on welfare indicators of 6-7 mo old beef calves following a 20-h transport. Three hundred and twenty-eight weaned calves (237 ± 29.7 kg of BW) were randomly assigned to a 2 × 2 × 2 nested factorial design: conditioning, conditioned (C) or non-conditioned (N); rest, 0 (R0) or 8 (R8) h, and post-rest transport, 4 (T4) or 15 (T15) h. Calves were sampled before (LO1) and after (UN1) the initial 20-h journey, before (LO2) and after (UN2) the additional 4 or 15-h journey, and at 1, 2, 3, 5, 14, and 28 d after UN2. Data was analyzed using the GLIMMIX procedure of SAS. Fixed effects included conditioning, transport, and time nested within rest period, while random effects included animal and pen. Greater shrink (p < 0.01) was observed in C than N calves after the initial 20-h transport. During the first week after transportation, the mean ADG of N calves was greater than C calves (p < 0.01). From d 14 to d 28, however, the mean ADG of C calves was greater than N calves (p < 0.01). Flight speed, cortisol and L-lactate concentrations were greater (p ≤ 0.05) in C than N calves between LO1 and d 5, while greater (p ≤ 0.02) non-esterified fatty acids, creatine kinase, serum amyloid-A, and haptoglobin concentrations were observed in N than C calves between LO1 and d 3. The R8-T4 calves had greater (p < 0.01) ADG than R8-T15 calves between LO1 and d 5. The R0-T4 calves had greater L-lactate concentrations than R0-T15 and R8-T4 calves (both p = 0.02) on d 1. The R0 calves had greater (p < 0.01) ADG than R8 calves between 14 and 28 d. This study suggests that C calves are better fit for transport than N calves as evidenced by behavioural and physiological parameters. Fewer and inconsistent differences were observed for rest and post-rest transport treatments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".