Swimming performances in long distance open-water events with and without wetsuit
Bibliographic record
Abstract
BACKGROUND: Existing literature showed improved swimming performances for swimmers wearing wetsuits competing under standardized conditions in races held in pools on short to middle distances. Data about the influence of wetsuits on swimming performances in long and ultra-long open-water swimming races are missing. It is unknown whether the benefit of wearing wetsuits is comparable in men and women. The aim of this study was to investigate the influence of wearing a wetsuit on open-water swimming performances at the 26.4 km 'Marathon Swim in Lake Zurich' in Lake Zurich, Switzerland, and the 3.8 km Lake Ontario Swim Team-Race (LOST-Race) in Lake Ontario, Canada. METHODS: Race times of the fastest female and male swimmers competing with and without wetsuit were compared using multi-level regression analyses and analysis of variance. RESULTS: In the 'Marathon Swim' in Lake Zurich, wearing a wetsuit had no effect on race time regarding the gender where athletes wearing a wetsuit were not faster than athletes without wetsuit. However, the ten fastest men wearing a wetsuit (410.6 ± 26.7 min) were faster (32.7%, p < 0.01) than the ten fastest women without wetsuit (544.9 ± 81.3 min). In the 'LOST-Race', the top ten men wearing a wetsuit (51.7 ± 2.5 min) were faster (13.2%, p < 0.01) than the top ten women wearing a wetsuit (58.5 ± 3.2 min). Additionally, the top ten men without wetsuit (52.1 ± 2.4 min) were faster (19.6%, p < 0.01) than the top ten women without wetsuit (62.3 ± 2.5 min). The top ten women wearing a wetsuit (58.5 ± 3.2 min) were faster (6.5%, p < 0.01) than top ten women without a wetsuit (62.3 ± 25 min). CONCLUSIONS: These results suggest that wearing a wetsuit had a positive influence on swimming speed for both women and men but the benefit of the use of wetsuits seemed to depend on additional factors (i.e. race distance). Women seemed to benefit more from wearing wetsuits than men in longer open-water ultra-distance swimming races.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".