Doping Control Analysis of Total Carbon Dioxide (TCO<sub>2</sub>) in Equine Plasma by Headspace Gas Chromatography–Mass Spectrometry (HS‐GC/MS)
Bibliographic record
Abstract
ABSTRACT The use of alkalinising agents prior to racing for manipulating performance in the horse has been identified since the 1990s. To mitigate the risk, an international threshold for available carbon dioxide in equine plasma based on analyses using the Beckman Synchron EL ‐ISE analyser was adopted in 1994 by the International Federation of Horseracing Authorities (IFHA) and revised from 37 to 36 mM in 2004. In 2009, the technical support for the above instrument was discontinued by its manufacturer. Based on the same measurement principle (i.e., ion selective electrode), the Beckman DxC600 analyser was selected as an alternative and validated against the protocol developed by the Association of Official Racing Chemists (AORC). Recently, the DxC600 analyser is also no longer supported by Beckman. Various alternative methods for measuring total carbon dioxide (TCO 2 ) in plasma have been explored. Among these, a headspace gas chromatography–mass spectrometry (HS‐GC/MS) method was first reported by the Analytical Forensic Testing Laboratory (AFTL) in 2017. Methods based on the same measurement principle were later developed by different horseracing laboratories. With the objective of cross‐validating the new HS‐GC/MS methods and to establish an absolute (rather than instrument‐dependent or empirical) threshold, an international research collaboration was initiated among different racing laboratories. This paper describes the results of cross‐validation studies conducted in November 2019 and December 2022 using horse administration samples from Canada and France, respectively, the determination of a threshold based on population data, and some technical insights on the HS‐GC/MS methods.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.012 |
| 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) | 0.000 | 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".