Female Athlete Triad Coalition cumulative risk assessment tool: proposed alternative scoring strategies
Bibliographic record
Abstract
We (i) identified alternative scoring strategies for the Female Athlete Triad Coalition cumulative risk assessment (CRA) tool to be utilized when particular risk factors (bone mineral density (BMD), oligomenorrhea/amenorrhea) cannot be determined; (ii) objectively defined dietary restriction for use in the CRA tool; and (iii) explored proxy measures of energy deficiency. This cross-sectional investigation of exercising women (n = 166) utilized an existing database derived from multiple studies designed to assess health, exercise, and menstrual function. Data from the screening/baseline period of each study included: anthropometrics, dual-energy X-ray absorptiometry, disordered eating questionnaires, descriptive data, and proxy measures of energy deficiency (total triiodothyronine (TT3) and ratio of measured-to-predicted resting metabolic rate (mRMR/pRMR)). Substituting delayed menarche for BMD was the best-fit replacement resulting in 15 (9%) participants being categorized in different clearance categories. When menstrual status cannot be assessed, such as during hormonal contraceptive use, low energy availability (EA) determined using self-report and disordered eating questionnaires was the best substitution, resulting in 34 (20%) participants being categorized in different clearance categories. Based on original clearance categorizations, the provisional group had lower TT3 (78.3 ± 2.2 ng/dL; 92.7 ± 2.7 ng/dL) and Harris–Benedict mRMR/pRMR (0.85 ± 0.01; 0.90 ± 0.01) than the full group. Until an updated risk assessment tool is developed, delayed menarche can substitute for low BMD and low EA for oligomenorrhea/amenorrhea. Novelty This investigation addresses previous limitations of the Triad CRA tool. Disordered eating questionnaires can be used to objectively identify dietary restriction for the low EA risk factor. When a risk factor cannot be assessed, delayed menarche can substitute for low BMD and low EA for oligomenorrhea/amenorrhea.
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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 | 0.038 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".