Collegiate male athletes exhibit conditions of the Male Athlete Triad
Bibliographic record
Abstract
The primary purpose of this study was to determine prevalence of the Male Athlete Triad (MAT) conditions: low energy availability (EA), low bone mineral density (BMD), and low testosterone in male collegiate athletes from different sports. Participants included 44 collegiate male athletes (age, 20.4 ± 0.2 years; body mass index, 25.3 ± 1.3 kg/m2) from 7 sports (cross country, soccer, basketball, wrestling, track, golf, and baseball). Resting metabolic rate, 3-day food intake, 7-day exercise energy expenditure, body composition, and reproductive and metabolic hormones were assessed. Of the total participants, 15% had low EA, 0% had low BMD, 28% had low total testosterone (TT), and 80% had low calculated free testosterone (cFT). There were no significant correlations between EA, BMD, TT, and cFT. Insulin and sex hormone binding globulin (SHBG) were below and on the upper end of the reference range for healthy male adults, respectively. Insulin was negatively correlated with total (r = –0.330, p = 0.043) and lumbar spine BMD z-scores (r = –0.413, p = 0.010). Low TT and low cFT were the most prevalent MAT conditions among all athletes. Further research should investigate the relationship between insulin and SHBG and the role of these hormones in the MAT. Novelty: Assessment of energy availability alone is not sufficient to identify physiological disturbances in collegiate male athletes. Low total and/or free testosterone may be present in some collegiate male athletes, regardless of BMD status. Low insulin and high SHBG concentration may portray the presence of conditions of the MAT in male collegiate 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".