Effect of season, facilities, and handling on grain-finished calves’ behaviour during trailer loading for transport
Bibliographic record
Abstract
This study examined how loading conditions and barn setup influence grain-fed calves' behaviour and the duration of loading in a commercial setting. It included 754 calves of various breeds—Holstein, Holstein × Angus, or others—with an average carcass weight of 176.8 ± 6.1 kg. Thirty-five loading events took place at thirteen farms in Quebec, following a preliminary audit assessing performed the farm characteristics, such as the loading dock, ramp, and layout. Calves were moved in small groups to trailers (regular or pot-belly), with observations recorded for the entire group. The presence of a loading dock reduced calf turns ( P = 0.003) and falls ( P = 0.084), while prior mixing significantly decreased the turnarounds ( P = 0.009) and stops ( P = 0.003). Falls occurred less frequently when aisle widths were between 0.70 and 1.20 m ( P = 0.029). Loading duration was shorter when a ramp was used ( P = 0.018) and when prior mixing had taken place ( P = 0.006). Overall, the findings suggest that the incorporating a loading dock, ramp and prior mixing as well as maintaining optimal aisle widths, can enhance calf welfare during loading. These adjustments could improve efficiency and reduce stress-related behaviours in commercial operations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".