Epidemiologic characteristics of catastrophic musculoskeletal injuries in Thoroughbred racehorses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To determine characteristics, incidence rate, and possible associations with selected demographic characteristics of catastrophic musculoskeletal injuries (CMIs) in Thoroughbred racehorses. ANIMALS: 76 Thoroughbreds with CMIs. PROCEDURES: Incidence rates of CMIs during racing or training were calculated with number of CMIs as the numerator and overall numbers of races or training events during 2004 and 2005 as the denominators. Exact 95% confidence intervals were calculated. Associations between incidence and dichotomous exposure factors, nominal factors, and ordinal factors were determined. Only univariable associations were examined. RESULTS: 76 horses were euthanized because of CMI and represented 2.36 and 1.69 deaths/1,000 racing starts in 2004 and 2005, respectively. Of these, 57 were euthanized within 60 days before or after a race, which yielded a point incidence of 1.05/1,000 racing starts and 0.39/1,000 training starts. CONCLUSIONS AND CLINICAL RELEVANCE: Incidence rate of CMIs at 2 Ontario racetracks was similar to that at other North American racetracks. A cumulative death rate of 1 to 2 deaths/wk should be considered typical when designing prevention strategies and offers a baseline value for measuring improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.022 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it