313 Effects of transport time and rest stop duration on welfare indicators of beef cattle travelling by road
Bibliographic record
Abstract
Abstract Forthcoming revisions to Canadian Transport regulations indicate un-weaned and weaned calves can be transported a maximum of 12 and 36 h, respectively, before an 8 h rest is required. The aim of this study was to assess the effect of rest duration after 12 and 36 h of transport on physiological and behavioral indicators of welfare in 7–8 mo old beef calves. Three hundred and twenty weaned calves (258 ± 23.9 kg BW) were randomly assigned to a 2 × 4 factorial design: 12 and 36 h of transport; and 0 (R0), 4 (R4), 8 (R8), and 12 (R12) h of rest. After the resting period animals were transported for an additional 4 h. A subset of 12 animals/treatment were sampled for non-esterified fatty acids (NEFA), haptoglobin and lactate concentrations prior to, and after the first and the 4 h transport, and 7 h, 2 and 28 d after the 4 h transport. Standing and lying behavior was assessed for 14 d after transport. Data was analyzed using the GLIMMIX procedure of SAS, where transport, and time nested within rest period were fixed effects and animal was a random effect. NEFA concentrations were greater (P < 0.01) in 12-R4 than 12-R8 and 12-R12 calves, while 36-R0 calves had greater (P ≤ 0.05) NEFA concentrations than 36-R4, 36-R8 and 36-R12 calves after the 4 h transport. Haptoglobin concentrations were greater (P < 0.01) in 36 than 12 h calves. No differences (P > 0.10) were observed for lactate. The day after transport, 36-R8 calves spent more (P < 0.01) time lying than 12-R8 calves. Overall, physiological indicators were greater in calves transported for 36 than 12 h, while no differences were observed between rest stops with the exception of NEFA, where overall concentrations were greater after shorter than longer rest periods.
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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) | 0.000 | 0.001 |
| 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) | 0.002 | 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".