Management factors affecting stereotypies and body condition score in nonracing horses in Prince Edward Island.
Bibliographic record
Abstract
In North America, there are few representative data about the effects of management practices on equine welfare. In a randomized survey of 312 nonracing horses in Prince Edward Island (response rate 68.4%), owners completed a pretested questionnaire and a veterinarian examined each horse. Regression analyses identified factors affecting 2 welfare markers: body condition score (BCS) and stereotypic behavior. Horses' BCSs were high (mean 5.7, on a 9-point scale) and were associated with sex (males had lower BCSs than females; P < 0.001) and examination date (P = 0.052). Prevalences of crib biting, wind sucking, and weaving were 3.8%, 3.8%, and 4.8%, respectively. Age (OR = 1.07, P = 0.08) and hours worked weekly (OR = 1.12, P = 0.03) were risk factors for weaving. Straw bedding (OR = 0.3, P = 0.03), daily hours at pasture (OR = 0.94, P = 0.02), and horse type (drafts and miniatures had a lower risk than light horses; P = 0.12) reduced the risk of horses showing oral stereotypies. Some of these results contradict those of other studies perhaps because of populations concerned.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".