The effect of cooling prior to and during exercise on exercise performance and capacity in the heat: a meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
Exercise is impaired in hot, compared with moderate, conditions. The development of hyperthermia is strongly linked to the impairment and as a result various strategies have been investigated to combat this condition. This meta-analysis focused on the most popular strategy: cooling. Precooling has received the most attention but recently cooling applied during the bout of exercise has been investigated and both were reviewed. We conducted a literature search and retrieved 28 articles which investigated the effect of cooling administered either prior to (n=23) or during (n=5) an exercise test in hot (wet bulb globe temperature >26°C) conditions. Mean and weighted effect size (Cohen's d) were calculated. Overall, precooling has a moderate (d=0.73) effect on subsequent performance but the magnitude of the effect is dependent on the nature of the test. Sprint performance is impaired (d=-0.26) but intermittent performance and prolonged exercise are both improved following cooling (d=0.47 and d=1.91, respectively). Cooling during exercise has a positive effect on performance and capacity (d=0.76). Improvements were observed in studies with and without cooling-induced physiological alterations, and the literature supports the suggestion of a dose-response relationship among cooling, thermal strain and improvements in performance and capacity. In summary, precooling can improve subsequent intermittent and prolonged exercise performance and capacity in a hot environment but sprint performance is impaired. Cooling during exercise also has a positive effect on exercise performance and capacity in a hot environment.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it