Nutrition Considerations in Special Environments for Aquatic Sports
Bibliographic record
Abstract
Elite athletes who compete in aquatic sports face the constant challenge of arduous training and competition schedules in difficult and changing environmental conditions. The huge range of water temperatures to which swimmers and other aquatic athletes are often exposed (16-31 °C for open-water swimming), coupled with altered aquatic thermoregulatory responses as compared with terrestrial athletes, can challenge the health, safety, and performance of these athletes. Other environmental concerns include air and water pollution, altitude, and jetlag and travel fatigue. However, these challenging environments provide the potential for several nutritional interventions that can mitigate the negative effects and enhance adaptation and performance. These interventions include providing adequate hydration and carbohydrate and iron intake while at altitude; optimizing body composition and fluid and carbohydrate intake when training or competing in varying water temperatures; and maximizing fluid and food hygiene when traveling. There is also emerging information on nutritional interventions to manage jetlag and travel fatigue, such as the timing of food intake and the strategic use of caffeine or melatonin. Aquatic athletes often undertake their major global competitions where accommodations feature cafeteria-style buffet eating. These environments can often lead to inappropriate choices in the type and quantity of food intake, which is of particular concern to divers and synchronized swimmers who compete in physique-specific sports, as well as swimmers who have a vastly reduced energy expenditure during their taper. Taken together, planned nutrition and hydration interventions can have a favorable impact on aquatic athletes facing varying environmental challenges.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".