Maintenance of bodyweight during a multiple‐day chuckwagon race meet
Bibliographic record
Abstract
The gruelling race schedules maintained by horses competing in chuckwagon racing raises concern for the horses' ability to recover quickly and continue to perform at a high level. The amount of bodyweight lost and the time required for recovery of this weight loss have been used to assess the level of stress imposed on horses competing in various multiple-day events. In this study, bodyweights were obtained from 40 Thoroughbred geldings (mean +/- s.e.; bodyweight 521.5 +/- 4.4 kg) before and after racing during a 5 day chuckwagon race meet. Body condition score (BCS) was determined on the first and last day of competition. Comparisons were based on the number of consecutive days the horse raced. Average bodyweight loss (P = 0.039) from each race was 3.5 +/- 0.3 kg (0.7% of initial bodyweight) and was not affected by the number of days the horse raced. The largest bodyweight deficit (P = 0.005) occurred within the 24 h period after their first race (5.3 +/- 0.5 kg; 1.0% of initial bodyweight). Horses racing on 2-5 consecutive days retained a 4.8 +/- 0.3 kg deficit (P = 0.01), which was maintained throughout the remainder of the race meet. Horses began and ended the race meet with a BCS of 4.9 +/- 0.2 and 4.7 +/- 0.2, respectively (using the 1 to 9 BCS system). Although chuckwagon horses compete in a strenuous event on several consecutive days, they appear to be managed well and have the ability to maintain their bodyweight despite the physical and psychological demands of frequent 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 | 0.000 | 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) | 0.001 | 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".