Quality Assurance and Proficiency Testing in the Canadian Equine Drug Control Program
Bibliographic record
Abstract
The Quality Assurance Program (QAP) administered by the Canadian Pari-Mutuel Agency (CPMA) has evolved over the past 17 years, in concert with the CPMA's equine drug research program. This program consists of site inspections, reports, and a check sample program. Participating laboratories also maintain internal quality control systems and are accredited for this scope of testing.The check sample program monitors routine screening and target testing of urine and blood for drugs using thin-layer chromatography or instrumental methods. The process is based on samples obtained after administration of drugs to horses, founded on results of CPMA's research. Common drugs in equine veterinary practice, and of interest in horse racing, are monitored. These include centrally active and cardiovascular drugs, diuretics and local anesthetics, respiratory and anti-inflammatory drugs, muscle relaxants and analgesics. The QAP provides a useful measure of laboratory performance for the Canadian racing industry.More recently, as part of the CPMA's partnership with Standards Council of Canada to accredit racing laboratories to ISO/IEC Guide 25, a proficiency test specific to this scope was implemented. Each cycle consists of 10 qualitative analysis samples of lyophilized, spiked equine urine, and 2 quantitative analysis samples of frozen, spiked equine serum or urine. For quantitative analysis, laboratory results must agree within ±20% of target or consensus mean value for drugs reported in the pg/mL range, or within ±40% for drugs reported in the ng/mL range. A reference laboratory prepares samples and conducts reference analysis. To date, 5 cycles of proficiency testing have been successfully completed by the participating labs.Program design and implementation activities, and results from both quality assurance and proficiency testing programs are presented and interpreted.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".