Welfare of horses transported to slaughter in Canada: Assessment of welfare and journey risk factors affecting welfare
Bibliographic record
Abstract
Roy, R. C., Cockram, M. S. and Dohoo, I. R. 2015. Welfare of horses transported to slaughter in Canada: Assessment of welfare and journey risk factors affecting welfare. Can. J. Anim. Sci. 95: 509-522. There is concern over the welfare of horses transported from the USA for slaughter in Canada. This study provides information on welfare issues associated with the transport of 3940 horses from 150 loads to a slaughter plant in Canada. Multivariable regression analyses were used to examine the association between journey characteristics and welfare outcomes. Injuries are considered in an accompanying paper. Five percent of the horses arrived from within Canada (median journey duration=12 h), and 95% arrived from five states in the USA (median journey durations 15-36 h). Seven percent of horses from Canada and 1% of horses from the USA arrived with pre-existing conditions. Five percent of the horses had a body condition score <3 (scale 1-5) and <1% were lame. Six horses from the USA (0.16%) arrived in a non-ambulatory condition. A linear mixed model showed that plasma total protein concentration increased with journey duration (P<0.001). No pre-transport measurements were possible and lairage and slaughter may have affected some of the results. Fewer severe welfare problems were identified than in similar studies conducted previously in the USA. However, multivariable analyses suggested that long journeys were associated with an increased risk of dehydration.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".