Air/CO2 cooling garment: Description and benefits of use for subjects exposed to a hot and humid climate during physical activities
Bibliographic record
Abstract
The severity of the hot and humid conditions to which miners are exposed increases as the depth of the work site increases. This can cause heat stress that can greatly affect the health and safety of workers. To resolve this, a cooling garment has been developed that uses an atmospheric discharge of liquid CO2 to create a cool microclimate with an average temperature of 12.5 (±0.4) °C beneath the garment. To evaluate the garment’s cooling efficiency, 19 male subjects participated in an experimental procedure. The two modes, cooling on and off, were compared. Significant physiological differences were found between the two modes after minute 27 (p < 0.05) until the end of the recovery phase for the heart rate (maximum difference of 10 beats per minute) and the internal body temperature (maximum difference of 0.33 °C). It was found that the modes also affected the subjects’ perceptions. The ON-mode was associated with better well-being and thermal comfort, and reduced humidity sensation. Perceptions of exertion were lower in the ON-mode condition from minute 2. The findings provide strong evidence of the ability of this cooling garment to reduce heat stress in hot and humid conditions similar to those encountered in deep mines.
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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 | 0.001 | 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".