The Use of Samples Originating From Doping Control Procedures for Research Purposes: A Qualitative Study
Bibliographic record
Abstract
Doping control samples may be used for research purposes by the World Anti-Doping Agency (WADA)-accredited laboratories after their compulsory storage period has expired. This study investigates opinions of stakeholders toward the governance of antidoping research on these samples and to evaluate the current framework. Semistructured interviews were conducted with stakeholders in antidoping research. The distinction between research and quality assurance in the International Standard for Laboratories (ISL) is neither well-understood nor interpreted uniformly by WADA-accredited labs. Most laboratories would not seek ethics approval for research on doping control samples. Interviewees considered that athletes should be better informed on what antidoping research can entail. A consistent and uniform approach toward the consent should be employed worldwide. Standards and safeguards should be implemented to reduce the risk of reidentification. Centralization of the Informed Consent Form in the ADAMS (Anti-Doping Administration & Management System) database would facilitate providing more information and allow the implementation of the right to withdraw.
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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 | 0.041 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.014 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".