Thermoregulatory Responses, Athlete Preparation And Knowledge Of Elite Open Water Swimming Competition In Divergent Environments.
Bibliographic record
Abstract
Elite open water swimming (OWS) competitions are conducted in various water temperatures (Tw; limits: 16-31 °C) thus presenting hypo- and hyper-thermic risk [Modest deviations (± 0.5-2 °C) in core temperature (Tc) have proven fatal]. The thermodynamic properties of water and blunted evaporative heat exchange exacerbate Tw derived challenges to ‘safe’ body temperature management and optimal performance. Despite OWS specific risk, limited: (i) Tc data in competition-relevant Tw’s; and (ii) knowledge of real-world and athlete adopted thermoregulatory aligned preparations for competition, are seen. PURPOSE: Characterise elite OWS Tc responses (ingestible telemetric pill), preparation, and aligned competition knowledge (via survey) to evidence-inform future thermoregulatory focused strategies to protect athlete health/performance. METHODS: In-race Tc was measured (n = 19; 13 male, 19.6 ± 2.6 yrs) at the LEN Open Water Cup (4th Leg; 18.2 °C, COLD) or the LEN Junior European OWS Championships (25.5 °C, WARM). Online survey also completed. RESULTS: Divergent individual Tc responses were seen (e.g., marked reductions and increases) within COLD/WARM (see Table 1 for central tendencies and dispersions). 33.3% (WARM) and 14.3% (COLD) trained in OWS settings ≤6 months annually with 58.3% (WARM) and 71.4% (COLD) using OWS settings only in summer months. 85.7% of (WARM) compared to 50% of (COLD) swimmers knew the predicted Tw for competition. 22.2% (WARM) used heat acclimation/acclimatisation (HA) strategies pre-competition. Of those who adopted HA in WARM, 11.1% suffered from negative symptomology related to body temperature in-race, compared to 33.3% who did not HA. CONCLUSION: Divergent Tc responses were evident within both COLD/WARM races. HA appears to offer some protection against undesired body temperature related symptomology. Therefore, individualised thermoregulatory competition practises are required alongside germane educational initiatives. Table 1: - Central Tendency and Dispersion of Race Tc Warm Event (n = 12, 9 male) Cold Event (n = 7, 4 male) Mean Race Tc (min-max) 38.1 °C (36.7 - 39.0 °C) 37.6 °C (35.5 - 38.7 °C) Mean Maximum Tc (min-max) 38.9 °C (38.2 - 39.5 °C) 38.4 °C (37.5 - 39.0 °C) Mean Minimum Tc (min-max) 37.2 °C (35.8-38.1 °C) 36.9 °C (35.0 - 37.9 °C) This project was funded by LEN European Aquatics.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".