Overcoming the Challenge of Confident Identification Among Two Related Groups of 17-Methyl Steroids by GC–MS
Bibliographic record
Abstract
Tetrahydromethyltestosterone (THMT) and 20-hydroxymethyl-18-nortetrahydromethyltestosterone (20OHnorTHMT) are metabolites of the anabolic androgenic steroids methyltestosterone and metandienone. Both molecular structures are used as markers in anti-doping analysis. There are eight reasonable diastereomeric structures of each group relevant for metabolic purposes. Highly sophisticated mass spectrometers fail to confidently differentiate these closely related, yet non-isomeric and non-isobaric groups of molecules. Due to the low abundance of the molecular ion, high-resolution mass spectrometry provides shared fragment ions that challenge identification by extracted ion chromatograms out of full scan mode acquisitions. Further on, tandem mass spectrometry uses partly the same ion transitions for both groups of targeted analytes. Thus, a reliable chromatographic separation is absolutely necessary. Therefore, a gas chromatographic method using a DB-5 ms capillary column (30 m, 0.25 mm, and 0.25 µm) was developed. Hence, discrimination between the two groups was enabled, and a confident structural assignment among the eight diastereomers was achieved. This case study contributes to a higher quality of anti-doping analysis, but even further raises awareness of the importance of chromatographic separation in cases of insufficient mass spectrometric discrimination.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".