Body composition and hydration status changes in male and female open-water swimmers during an ultra-endurance event
Bibliographic record
Abstract
Body mass changes during ultra-endurance performances have been described for running, cycling and for swimming in a heated pool. The present field study of 20 male and 11 female open-water swimmers investigated the changes in body composition and hydration status during an ultra-endurance event. Body mass, both estimated fat mass and skeletal muscle mass, haematocrit, plasma sodium concentration ([Na+]) and urine specific gravity were determined. Energy intake, energy expenditure and fluid intake were estimated. Males experienced significant reductions in body mass (-0.5 %) and skeletal muscle mass (-1.1 %) (P < 0.05) during the race compared to females who showed no significant changes with regard to these variables (P > 0.05). Changes in percent body fat, fat mass, and fat-free mass were heterogeneous and did not reach statistical significance (P > 0.05) between gender groups. Fluid intake relative to plasma volume was higher in females than in males during the ultra-endurance event. Compared to males, females' average increase in haematocrit was 3.3 percentage points (pp) higher, urine specific gravity decrease 0.1 pp smaller, and plasma [Na+] 1.3 pp higher. The observed patterns of fluid intake, changes in plasma volume, urine specific gravity, and plasma [Na+] suggest that, particularly in females, a combination of fluid shift from blood vessels to interstitial tissue, facilitated by skeletal muscle damage, as well as exercise-associated hyponatremia had occurred. To summarise, changes in body composition and hydration status are different in male compared to female open-water ultra-endurance swimmers.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".