A light-weight cooling vest enhances performance of athletes in the heat
Bibliographic record
Abstract
During the 1990s, emphasis on the health and safety of people who exercise in hot, humid conditions increased and many organizations became aware of the need for protection against heat-related disorders. A practical, pre-cooling strategy applicable to several sporting codes, which is low cost, easy to use, light-weight and which enhances cooling of the human body prior to and following exercise, was developed and tested. Eight males and eight females participated in a maximal oxygen consumption (VO2max) test and four trials: a control (without cooling) and wearing each of three different cooling vests (A, B, C). Vests were worn during the rest, stretch, warm-up (50% VO2max) and recovery stages of the protocol, but not during the 30 min run (70% VO2max). Core and skin temperatures during exercise were reduced (by approximately 0.5 degrees C, rectal; 0.1-1.4 degrees C, abdominal skin temperature) and sweat rates were lower (by approximately 10-23%). Endurance times for running at 95% of VO2max were increased by up to 49 s. Perceptions of the thermal state and skin wetness showed changes to greater levels of satisfaction. Physiological and sensory responses were related to design features of the vests.
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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".