O-367 EVALUATING THE EFFECTIVENESS AND COMFORT OF NEW MOISTURE BARRIERS AND DESIGNS FOR FIREFIGHTERS’ PERSONAL PROTECTIVE CLOTHING
Bibliographic record
Abstract
Abstract Introduction Firefighters face heat stress in the course of their duties, exposing them at increased risk of cardiovascular accidents, their most common cause of death. Firefighters’ personal protective clothing (PPC) contributes to the physiological stress by retaining body heat and moisture within the various layers, preventing sweat evaporation and thus increasing body temperature and the risk of cardiovascular events. Methods The aim of this study was to determine the effects of new moisture barriers and firefighter PPC designs during physiological, psychophysical and movement assessment. Results Ten participants performed treadmill walking tests in a climate chamber (35°C, 50% relative humidity). Five PPC were tested, comprising different combinations of two moisture barriers, two designs (Traditional, Innovative), and an air circulation system. Oxygen consumption, heart rate, core temperature, humidity and temperature inside the PPC, psychophysical perceived exertion and ease of movement were measured. The modifications to the outer shell of the Innovative model did not reduce physiological stress during exercise. The temperature in the inner layer of this model was significantly higher than in the Traditional model. The modifications were more uncomfortable and restrictive during movements. Perceived exertion showed a significant difference between the two moisture barriers. The air circulation system did not reduce thermal stress, and seemed more restrictive during movements. The results of this research demonstrate the importance of improving the effectiveness of PPC. Discussion-Conclusion Measurements of temperature and relative humidity inside layers seem to be a good indicator for assessing the PPC performance in reducing thermal stress associated with the microclimate formed inside the PPC.
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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 | 0.003 | 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 | 0.001 | 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) | 0.000 | 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".