PSXV-16 Association of Experience and pre-Race Behavior in Performance Among Racing Quarter Horses
Bibliographic record
Abstract
Abstract The annual average cost of maintaining a racehorse will typically outweigh its earning, making it important that the horse performs above average. The goal of this study was to investigate if the age or experience level of a racehorse could be associated with performance. This study observed pre-racing Quarter Horses (n = 1,033) behavior during one racing season at Delta Downs racetrack (Vinton, LA). The horses were placed into groups based on race experience (0-2, 3-10, and 11+ total races). Horse pre-race before saddling (BSAD), saddling (SAD), after saddling (ASAD) and post-parade (POST) behaviors (calm, ready or nervous) were observed to identify if the horse was calm, ready, or nervous. The behavior types were recorded as categorical variables in this study and were analyzed using proc FREQ, and the finish was recorded as a quantitative variable and were analyzed using proc GLM with (P < 0.05) being statistically different. Horses with 11+ races had a mean±SE finish (4.9±0.1), better (P< 0.05), than horses with 3 to 10 races (4.8±0.2) and both were better (P< 0.05) than horses with 0 to 2 races experience (5.5±0.2). Race experience was also associated with pre-race behaviors. There were more (P< 0.05) horses with 0 to 2 races experience that were classified as nervous during the BSAD (39/326, 11.9%), SAD (29/326, 8.9%), ASAD (13/325, 4.0%) and POST (17/320, 5.3%) compared with horses with 11 plus races experience; BSAD (5/343, 1.5%), SAD (16/343, 4.7%), ASAD (4/343, 1.2%) and POST (1/341, 0.3%). The improvement in race finish among horses with more experience could be that they have been placed in more suitable levels of racing competition compared with unexperienced horses. However, the additional racing experience was associated with less stress or fear-full behaviors pre-race that can result in a reduction of available energy to possibly prolonged elevated cortisol concentrations.
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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 | 0.000 | 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) | 0.006 | 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".