5 Effect of rest stop on welfare indicators of conditioned and non-conditioned ranch-direct or auction-market-sourced beef cattle, transported by road
Bibliographic record
Abstract
Abstract The aim of this study was to assess the effect of an 8h rest stop after 36 h of road transport on physiological and behavioral indicators of welfare in 7–8-mo-old conditioned and non-conditioned beef calves, sourced from either a ranch or an auction market. Three hundred and twenty weaned calves (245 ± 35.7 kg BW) were randomly assigned to a 2 × 2 × 2 factorial design: conditioning, conditioned (C) or non-conditioned (N); source, ranch direct (R) or auction market (A); and rest, 0 (R0) or 8 (R8) h. After resting, animals were transported for an additional 4 h. A subset of 12 animals/treatment were sampled for non-esterified fatty acids (NEFA), serum amyloid-A (SAA) and creatine kinase (CK) concentrations prior to the first loading (L1); after 36 h of transport; prior to and after the additional 4 h of transport, on the day of arrival (0); and 1, 2, 3, 5, 14, and 28 d after the 4h transport. Daily standing % and dry matter intake (DMI) were assessed for 3 d after transport. Data were analyzed using the GLIMMIX procedure of SAS. Fixed effects included conditioning, source, and time (nested in rest), while random effects were animal and pen. At L1, mean concentrations of NEFA, SAA and CK were greater (P < 0.05) for N-R0 than C-R0 and for N-R8 than C-R8. The N and R groups had greater (P < 0.05) standing % than the C and A groups, respectively. On d 0 and 1, the C-R0 and C-R8 groups had greater (P < 0.05) DMI than the N-R0 and N-R8 groups, respectively. Overall, physiological and behavioral indicators of welfare were greater in conditioned than non-conditioned calves, while fewer differences were observed between ranch and auction market calves, as well as rested or unrested calves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".