Annual banned‐substance review: analytical approaches in human sports drug testing
Bibliographic record
Abstract
International anti-doping efforts are harmonized and regulated under the umbrella of the World Anti-Doping Code and the corresponding Prohibited List, issued annually by the World Anti-Doping Agency (WADA). The necessity for a frequent and timely update of the Prohibited List (as the result of a comprehensive consultation process and subsequent consensual agreement by expert panels regarding substances and methods of performance manipulation in sports) is due to the constantly growing market of emerging therapeutics and thus new options for cheating athletes to illicitly enhance performance. In addition, 'tailor-made' substances arguably designed to undermine sports drug testing procedures are considered and the potential of established drugs to represent a doping substance is revisited in light of recently generated information. The purpose of the annual banned substance review is to support doping controls by reporting emerging and advancing methods dedicated to the detection of known and recently outlawed substances. This review surveys new and/or enhanced procedures and techniques of doping analysis together with information relevant to doping controls that has been published in the literature between October 2010 and September 2011.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".