Low Energy Availability and Relative Energy Deficiency in Sport: What Coaches Should Know
Bibliographic record
Abstract
The Female Athlete Triad (Triad) and the more encompassing Relative Energy Deficiency in Sport (RED-S) are disorders caused by low energy availability (LEA). LEA is a state of insufficient energy intake by an athlete relative to their energy expenditure. Persistent LEA results in the deleterious consequences to health and performance that comprise RED-S. With respect to both the Triad and RED-S, researchers have called for more education of those involved with sport, particularly coaches, to help reduce the incidence of these disorders. Recent studies have shown that as few as 15% of coaches are aware of the Triad, with up to 89% unable to identify even one of its symptoms. RED-S is a more recently established concept such that coach knowledge regarding it has only begun to be assessed, but the results of these initial studies indicate similar trends as for the Triad. In this review, we synthesize research findings from 1986 to 2021 that pertains to LEA and RED-S, which coaches should know so they can better guide their athletes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".