Application of FAIMS to anabolic androgenic steroids in sport drug testing
Bibliographic record
Abstract
Mass spectrometric identification of anabolic androgenic steroids challenges standard doping-control methods. To reveal a doping offence the presence of prohibited anabolic androgenic steroids at trace levels in the picogram-per-millilitre range must be confirmed as reliable. Human urine samples containing epitrenbolone, metandienone metabolite (17beta -hydroxymethyl-17alpha-methyl-18-norandrost-1,4,13-trien-3-one), stanozolol, 16beta-hydroxystanozolol and 4beta-hydroxystanozolol were analysed using LC-FAIMS-MS/MS. These substances are prohibited in sport according to World Anti-Doping Agency (WADA) regulations. Glucuronides were hydrolysed and prepared by liquid-liquid extraction. Excellent recovery and precision were obtained for all compounds. Linear calibration results for epitrenbolone and metandienone metabolite were obtained and concentration information could be determined in the ranges of reliable response between 750-1200 and 100-600 pg/mL, respectively. Limits of detection were estimated at 25 pg/mL (stanozolol), 50 pg/mL (metandienone metabolite, 16beta-hydroxystanozolol), 100 pg/mL (4beta-hydroxystanozolol) and 500 pg/mL (epitrenbolone). The assay was applied to doping-control samples. For all analytes, LC-FAIMS-MS/MS resulted in excellent interference removal, which effectively extends the post-dose detection time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".