Evaluation of Minimum Reporting Limits to Determine In‐Competition Use of Stimulants
Bibliographic record
Abstract
The applicability of urinary minimum reporting limits (MRLs) to determine in-competition use of prohibited substances is an evolving topic. Most stimulants are subject to a universal MRL, despite the wide range of commercially available dosages for commonly used stimulants. Further, it is unknown whether the urinary MRL is reflective of a pharmacological dose ingested after the start of the in-competition period. To evaluate whether urinary MRLs can distinguish between in-competition and out-of-competition use, a controlled administration study was performed with three commonly used stimulants-amphetamine, methylphenidate, and modafinil at relatively low but therapeutically relevant dosages. Four to six volunteers were administered a particular drug once per day for five consecutive days. Urine, serum, dried blood spots (DBS), and oral fluid (OF) were collected during the active administration period and for 48 h after cessation of use. For all participants, urinary concentrations for all target analytes exceeded the MRL even 48 h after cessation of use. In serum and DBS, most volunteers showed detectable amounts at 48 h post use. Peak concentrations were variable between target compounds even with similar administered dosages. Further, there was a reproducible difference between serum and DBS concentrations. Interpretation of results from OF measurements was challenging due to the inability to normalize for hydration status and OF viscosity. Analyte concentrations decreased steadily over the washout period but did not correlate across matrices for all target analytes. The study reiterates the challenges associated with determining in-competition use by relying on urinary concentrations.
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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 | 0.232 | 0.251 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".