The effect of hand cooling during intermittent training of elite swimmers.
Bibliographic record
Abstract
BACKGROUND: The aim of this paper was to determine the effects of using intermittent hand cooling during high intensity, intermittent training on thermoregulatory, performance and psychophysical variables in elite level swimmers in a training pool (30.5±0.5 °C). METHODS: Randomized cross-over design. Following a standard warm-up, ten male swimmers (20.3±3.2 years) were instructed to maintain the fastest 100-m time (on average) for an 8 x 100 m freestyle swimming set performed either in a training pool with cooling (TPC) or a training pool with no-cooling (TPNC). Time at 100 m, core temperature (Tc), heart rate (HR), ratings of perceived exertion (RPE), thermal comfort (ThC) and thermal sensation (ThS) were recorded following each repetition. Participants were cooled during the 90 s rest interval between repetitions using the Rapid Thermal Exchange System (RTX) (AVAcore Technologies Inc., Ann Arbor, MI, USA). RESULTS: There was a better performance when comparing 100 m time (1.50±1.98 s faster) for the final repetition in the TPC condition compared to the final repetition in the TPNC condition (P<0.05). There was no significant difference between Tc, HR, RPE, ThC and ThS (P<0.05). CONCLUSIONS: There was a performance benefit in the last set of the training block in the TPC condition that could not be attributed to any of the physiological and psychophysical measures used in the study.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".