Physiological aspects and clinical sequelae of energy deficiency and hypoestrogenism in exercising women
Bibliographic record
Abstract
Amenorrhoea associated with reduced caloric intake and strenuous exercise leads to hypoestrogenism and is associated with clinical manifestations that include disordered eating, stress fractures, osteoporosis, and, as recently reported, a potential increase in the risk of premature cardiovascular disease. Disordered eating, menstrual irregularities and bone loss comprise the clinical condition known as the 'female athlete triad'. The aetiology of the triad is linked to a high prevalence of disordered eating and cognitive restraint. This results in inadequate caloric intake for high exercise energy expenditures that leads to energy deficiency. This in turn stimulates compensatory mechanisms, such as weight loss or energy conservation, subsequently causing a central suppression of reproductive function and concomitant hypoestrogenism. Because the aetiology of menstrual disturbances and the female athlete triad is causally linked to energy deficiency, there is no justification for fears that exercise itself is unhealthy for women. However, improved detection, monitoring, and treatment of all components of the triad in exercising women should be emphasized. This paper critically reviews the physiological aspects and clinical sequelae of energy deficiency and hypoestrogenism associated with the female athlete triad in exercising women.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".