Nandrolone excretion in sedentary vs physically trained young women
Bibliographic record
Abstract
We investigated the effects of the menstrual cycle, oral contraception and physical training on exhaustive exercise-induced changes in the excretion of nandrolone metabolites [19-norandrosterone (19-NA), and 19-noretiocholanolone (19-NE)] in young women. Twenty-eight women were allocated to an untrained group (n=16) or a trained group (n=12), depending on their physical training background. The untrained group was composed of nine oral contraceptive users (OC+) and seven eumenorrheic women (OC-), while the trained group was entirely composed of OC+ subjects. Three laboratory sessions were conducted in a randomized order: a prolonged exercise test, a short-term exercise test and a control session. Urine specimens were collected before and 30, 60 and 90 min after the exercise test and at the same times of the day during the control session. Urinary concentrations of nandrolone metabolites were determined by gas chromatography coupled to mass spectrometry. Urinary concentrations of 19-NA and 19-NE ranged from undetectable levels to 1.14 and 0.47 ng/mL, respectively. Nandrolone excretion was not affected by the menstrual cycle phase (early follicular vs mid-luteal), prior physical training, oral contraception or acute physical exercise. Therefore, a urinary concentration of 2 ng/mL of 19-NA appears to be fair as the upper acceptable limit in doping control tests for female athletes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".