Evaluation of catastrophic musculoskeletal injuries in Thoroughbreds and Quarter Horses at three Midwestern racetracks
Bibliographic record
Abstract
OBJECTIVE: To determine the incidence of and compare the types of catastrophic musculoskeletal injuries (CMIs) sustained in Thoroughbreds and Quarter Horses during racing at 3 Midwestern racetracks from 2000 to 2006. DESIGN: Retrospective cohort study. ANIMALS: 139 Thoroughbred and 50 Quarter Horse racehorses euthanized because of CMIs. PROCEDURES: Veterinary officials from 3 Midwestern racing jurisdictions provided injury reports for Thoroughbreds and Quarter Horses that sustained CMIs (which required euthanasia) and the total number of race starts for each year. The number of CMIs/1,000 starts was determined for each racetrack. Past performance reports for each horse with a CMI were evaluated. RESULTS: The total number of race starts (both breeds) at the 3 racetracks from 2000 through 2006 was 129,460, with an overall incidence of 1.46 CMIs/1,000 race starts. Incidences of CMIs among racetracks were similar. Of horses that sustained a CMI, the median age of Thoroughbreds at first race was 3 years, compared with a median age of 2 years for Quarter Horses. A larger proportion of Thoroughbreds sustained a CMI in a claiming race than did Quarter Horses, and a larger proportion of Quarter Horses sustained a CMI in a futurity trial than did Thoroughbreds. The most common site for CMIs in Thoroughbreds was the left forelimb (69/124 [55.6%]), whereas most CMIs in Quarter Horses involved the right forelimb (18/30 [60.0%]). CONCLUSIONS AND CLINICAL RELEVANCE: Differences identified between CMIs in Thoroughbred and Quarter Horse racehorses should allow veterinarians to focus on horses and anatomic regions of greatest risk of CMI during racing.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".