Stable isotope ratio profiling of testosterone preparations
Bibliographic record
Abstract
Gas chromatography-combustion-isotope ratio mass spectrometry (GC-C-IRMS) is the preferred method of confirming the administration of exogenous testosterone by athletes. This relies on synthetic testosterone preparations being depleted in (13) C compared to natural testosterone. There is concern, however, about the existence of synthetic testosterone products that are unexpectedly (13) C-enriched and which may allow athletes to circumvent the current GC-C-IRMS test. Further to the reported studies of legitimate pharmaceutical-grade testosterone products, a detailed analysis of seized materials from border-level seizures was required to obtain intelligence concerning trends in 'black market' testosterone manufacture and distribution. The sample set collected for this study between 2006 and 2009 inclusive provided a δ(13) C range (n = 266) of -22.9‰ to -32.6‰ with mean and median values of -28.4‰ and -28.6‰, respectively. Within this distribution there were 24 samples (9%) confirmed to have δ(13) C values in the range reported for endogenous urinary steroid metabolites (≥ -25.8‰). The benefit of δ(13) C profiling for testosterone preparations was demonstrated by the ability to identify specific seized products that can be target tested for future intelligence purposes. In addition, the potential of stable hydrogen isotope ratio ((2) H/(1) H; δ(2) H) discrimination to complement δ(13) C analysis was investigated. Methodologies for the determination of δ(2) H values by gas chromatography-thermal conversion-isotope ratio mass spectrometry (GC-TC-IRMS) were developed to provide a δ(2) H range (n = 173) of -177‰ to -268‰ with mean and median values of -231‰ and -234‰, respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".