Elucidation of urinary metabolites of fluoxymesterone by liquid chromatography‐tandem mass spectrometry and gas chromatography‐mass spectrometry
Bibliographic record
Abstract
The suitability of liquid chromatography tandem mass spectrometry (LC-MS/MS) and gas chromatography mass spectrometry (GC-MS) for the elucidation of fluoxymesterone metabolism has been evaluated. Electrospray ionization (ESI) and collision induced dissociation (CID) fragmentation in LC-MS/MS and electron impact spectra (EI) in GC-MS have been studied for fluoxymesterone and two commercially available metabolites. MS(n) experiments and accurate mass measurements performed by an ion-trap analyser and a QTOF instrument respectively have been used for the elucidation of the fragmentation pathway. The neutral loss scan of 20 Da (loss of HF) in LC-MS/MS has been applied for the selective detection of fluoxymesterone metabolites. In a positive fluoxymesterone doping control sample, 9 different analytes have been detected including the parent compound. Seven of these metabolites were also confirmed by GC-MS including 5 previously unreported metabolites. On the basis of the ionization, the CID fragmentation, the accurate mass of the product ions and the EI spectra of these analytes, a tentative elucidation as well as a proposal for the metabolic pathway of fluoxymesterone has been suggested. The presence of these compounds has also been confirmed by the analysis of five other positive fluoxymesterone urine samples.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".