Bovine colostrum supplementation optimises earnings, performance and recovery in racing Thoroughbreds
Bibliographic record
Abstract
Bovine colostrum (BC) is the first milk produced by cows after calving and contains numerous beneficial substances for the immunity and development of the newborn calf. Because of the growth and immune factors in BC, it has become an attractive supplement for use by athletes to support immunity and health during athletic performance. In order to evaluate the effects of oral BC supplementation on equine athletes, this study evaluated the earnings, performance, recovery and incidence of upper respiratory infections (URTI) in racing horses. The study design was a randomized cross-over racing performance study. 21 horses in race training were randomly assigned to train and compete with or without BC supplementation. After each horse competed in three races, it was crossed over to the other group, allowed a three week washout period, and then competed in three additional races. Horses in public training stables of 3 participating trainers were used. Race performance as determined by earnings, Bloodstock Research Information System (BRIS) speed figures, recovery as determined by number of days between races and incidence of upper respiratory tract disease was recorded. 11 horses completed the study. There was no effect of the order of BC supplementation on the measured variables. Horses on BC supplementation earned $ 2,088 more purse money per race, than when unsupplemented ( P =0.016), and ran an average of 5 BRIS speed points higher ( P =0.03). Horses returned to racing on average 7.5 days faster (16.9 days vs 24.4 days, P =0.048). There were no URTI among the horses on BC supplementation and two infections while not on BC supplementation (z-test, P =0.11). Statistical analysis showed that horses recovered more quickly, earned three times more money and raced better as judged by BRIS scores while competing with BC supplementation. BC supplemented horses also experienced fewer URTI, although this effect was not significant.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".