Longitudinal evaluation of the isotope ratio mass spectrometric data: towards the ‘isotopic module’ of the athlete biological passport?
Bibliographic record
Abstract
The detection of the abuse of pseudo-endogenous steroids (testosterone and/or its precursors) is currently based on the application of the steroid module of the World Anti-Doping Agency (WADA) Athletes' Biological Passport (ABP), implemented through ADAMS. Diagnostic metabolites are monitored for every athlete and statistically evaluated with a predictive Bayesian approach. In the case of suspicious samples, the data of the ABP are confirmed and the isotope ratio mass spectrometry (IRMS) test is activated. We have previously demonstrated that IRMS enables confirmation of the non-endogenous origin of pseudo-endogenous steroids in otherwise non-suspicious samples, after a longitudinal evaluation of the ABP, even after the inclusion of additional long-term diagnostic hydroxylated metabolites, and that the delta values of the parameters obtained during the IRMS confirmation process presented much less variability compared to the parameters of the ABP. The aim of the present work is to evaluate the application of the same methodology used for the evaluation of the ABP, on the delta values of the pseudo-endogenous steroids monitored. The effectiveness of the proposed model has been assessed on samples obtained after controlled administrations of oral androstenedione and transdermal testosterone. The results support the conclusion that, if applied, the longitudinal evaluation of the IRMS data allows the detection of positive samples that otherwise will be reported as atypical findings (ATF), improving the efficacy of the fight against doping in sport. This approach, by narrowing the individual acceptable range, could possibly improve the detection of the intake of preparations of synthetic origin with delta values close to or overlapping those of endogenously produced steroids. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| 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".