Case Study: Atypical <i>δ</i><sup>13</sup>C values of urinary norandrosterone
Bibliographic record
Abstract
Abstract Isotope ratio mass spectrometry (IRMS) has been established in doping control analysis to identify the endogenous or exogenous origin of a variety of steroidal analytes including the 19‐norsteroid metabolite norandrosterone (NorA). NorA can be found naturally in human urine in trace amounts due to endogenous demethylation or in situ microbial degradation. The administration of nortestosterone (nandrolone) or different prohormones results in the excretion of urinary NorA. Usually, this can be detected by IRMS due to differing δ13C values of synthetic 19‐norsteroids compared to endogenous reference compounds. The consumption of uncastrated pig edible parts like offal or even meat may also lead to a urinary excretion of NorA. In order to determine the δ13C values of such a scenario, urine samples collected after consumption of a wild‐boar‐testicle meal were analyzed. IRMS revealed highly enriched δ13C values for urinary NorA, which could be related to the completely corn‐based nutrition of the animal. Isotopic analysis of the boar's bristles demonstrated a dietary change from C3‐based forage, probably in winter and spring, to a C4‐based diet in the last weeks to months prior to death. These results supported the interpretation of an atypical test result of a Central European athlete's doping control sample with δ13C values for NorA of −18 ‰, most probably caused by the consumption of a wild boar ragout. As stated before, athletes should be fully aware of the risk that consumption of wild boar may result in atypical or even adverse analytical findings in sports drug testing.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 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".