Postinjury performance for differing humeral stress fracture locations in the racing thoroughbred
Bibliographic record
Abstract
OBJECTIVE: To assess the influence of humeral stress fracture location on the time to return to racing and postinjury performance of thoroughbred racehorses. STUDY DESIGN: Retrospective study (1992-2015). SAMPLE POPULATION: Thoroughbred racehorses (n = 131) that presented for lameness with the sole diagnosis of humeral stress fractures in the lame limb, as determined by scintigraphy or radiology. METHODS: tests). Pre-stress and post-stress fracture performance for the three stress fracture locations were assessed: (1) earnings pre-stress and post-stress fracture (Kruskal-Wallis one-way analysis of variance), (2) average earnings per start prefracture, and (3) average earnings per start postfracture (Wilcoxon signed-rank tests). RESULTS: Stress fracture locations were caudodistal (n = 36), craniodistal (n = 43), and caudoproximal (n = 52). One hundred ten of 131 horses raced postfracture, and 54 of 131 horses raced prefracture. Age at injury was 43.61 months caudodistal, 33.48 months caudoproximal, and 36.65 months craniodistal. Horses returned to race at a median of 244 days (range, 218-272). Postfracture earnings per start were greater for caudodistal vs caudoproximal (P = .04). CONCLUSION: There were no differences in prefracture earnings or fracture site and sex or limb affected. Return-to-race time varied by location but not significantly. Differences in earnings preinjury and postinjury were not significant. Horses with a stress fracture at the caudodistal location earned significantly more compared with horses with a stress fracture at the caudoproximal location after they returned to race. CLINICAL SIGNIFICANCE: Thoroughbred racehorses have a good prognosis for return to racing regardless of fracture location.
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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) | 0.002 | 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".