Pooled Sampling Technique to Improve the Monitoring of Medication Use in the Racehorse Industry
Bibliographic record
Abstract
All anti-doping programmes face financial constraints and monitoring trends in medication use or abuse in a population of racehorses can be difficult and expensive. Obtaining biological samples is the primary method of anti-doping control in individual horses or stables of horses but can be invasive and expensive. Another important practice of anti-doping control has been the confiscation of used and filled syringes by regulators for individual forensic analysis. Pooled samples testing involves the testing of multiple individual samples together as one composite sample. This pooled sample approach has been employed to gather information concerning populations' exposure to substances and infectious agents including the analysis of samples of wastewater (a large, pooled sample) that have been used during the pandemic to monitor the presence of new COVID variants. Moreover, pooled samples of urine and wastewater have been used to monitor for recreational drug use and for the presence of new psychoactive substances in cities and large events. This approach has been credited with providing timely insight in the trends of illicit drugs use. To be effective, an anti-doping programme should not be predictable to avoid being defeated by countermeasures; therefore, the implementation of new methods is considered essential. A new pooled sampling technique using confiscated groups of used syringes and needles including biomedical sharps containers obtained from veterinarians and other horse racing industry participants has been employed over several years in Ontario, Canada. These containers held needles used to administer substances to racehorses along with syringes and other debris. The analysis of the wash provided a timely insight of medications being administered in horses, and substances present at racetracks and training centres including substances predominantly of human use and abuse. Sharp containers confiscated from veterinarians and trainers provided insight into injectable medications administered at numerous stables and to hundreds of horses.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".