Implementation and Performance of the Gas Chromatography/Combustion/Isotope Ratio Mass Spectrometry-Based Method for the Confirmatory Analysis of Endogenous Anabolic Steroids during the Rio de Janeiro Olympic and Paralympic Games 2016
Bibliographic record
Abstract
Carbon isotope ratio (CIR) confirmation is one of the most complex and delicate analyses in the doping control field, due to the nature of the molecules to be confirmed, normally present in urinary samples as a consequence of an endogenous production. The requirements for method validation established by the World Anti-Doping Agency (WADA) have been pushing the accredited laboratories to improve their methods. The choice of the method is always a cost benefit ratio involving a hard-working and time-consuming analysis and the guarantee of reporting of reliable results. This work presents the method fully validated by the Brazilian Doping Control Laboratory as part of the preparation for the Rio de Janeiro Summer Olympic and Paralympic Games 2016. Sample preparation encompassed solid-phase extraction, liquid-liquid extraction, enzymatic hydrolysis, acetylation, and purification by preparative high-performance liquid chromatography, and analyses were performed by gas chromatography/combustion/isotope ratio mass spectrometry. This proved to be a robust method to CIR confirmation in a big event, as demonstrated by the analysis of 179 samples during the Games 2016, from clearly negative results and adverse findings for testosterone (T) and related substances, boldenone and its metabolite, 19-norandrosterone and formestane. Two atypical findings were also reported for T and metabolites.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".