Ontario Racehorse Death Registry, 2003–2015: Descriptive analysis and rates of mortality
Bibliographic record
Abstract
BACKGROUND: The Province of Ontario maintains a registry of racehorse deaths occurring within 60 days of a race or trial entry that provides insight into mortality rates and costs of competition. OBJECTIVES: To characterise and quantify mortality and identify breed differences. STUDY DESIGN: Retrospective annualised cohort study. METHODS: The Ontario Death Registry for 2003-2015, containing 1713 cases, was audited and information on the relationship between death and official work added. Race and trial data from industry performance databases were used to determine mortality rates according to breed, year, age, sex and circumstances of death. RESULTS: Breed differences in mortality rate and individual risk were found. Thoroughbreds (Tb) had the greatest exercise-associated mortality (EAM) rate and risk by all measures (2.27 deaths/1000 race starts, 0.95-1.0% annual individual risk), followed by Quarter horses (Qh, 1.49, 0.60-0.69%). Rate and risk were lowest for Standardbreds (Sb, 0.28, 0.23-0.24%). Nonexercise annual individual risk was highest for the Sb (0.45%, vs. Tb 0.33%, and Qh 0.32%). Pattern and type of EAM mirrored the characteristics of competitive activity in each industry, with high Tb and Qh mortality being associated with exercise and involving musculoskeletal injuries, dying suddenly and accidents. Low Sb EAM reflected the more extensive nature of training preparation and racing for this breed. MAIN LIMITATIONS: Available data provided no information on morbidity, mortality beyond the 60-day horizon or for horses not racing. Numbers for the Qh were low. CONCLUSIONS: Race-intensity exercise is clearly hazardous for horses, with hazards varying widely between breeds and showing parallels with industry cultural and management norms. Breed differences provide insights concerning strategies that could reduce mortality, while improving welfare and reducing costs of participation. For all breeds, musculoskeletal injury was the major contributing cause of mortality.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".