A New Firefighting Simulation on a Treadmill in a Temperate Environment Induces Similar Physiological Responses to Those Reported for Live Fire Drills
Bibliographic record
Abstract
OBJECTIVE: The purpose was to characterize the physiological responses resulting from a newly developed treadmill firefighting simulation and to compare these responses with those induced by live fire and simulated firefighting activities reported in different studies. METHODS: Forty participants (four women) (25 ± 6 years) performed a 25-minute treadmill firefighting simulation that consisted of various tasks completed on a typical work-rest cycle at an imposed rhythm in a temperate environment (ambient temperature: 22.6°C ± 0.6°C, relative humidity: 29.7% ± 11.6%). RESULTS: Rectal temperature increased by 0.56°C ± 0.15°C; peak and mean oxygen consumption were 35.3 ± 3.3 and 20.8 ± 1.7 mL·kg -1 ·min -1 , respectively; and 1169 ± 182 L of air was used. CONCLUSION: These results show that the treadmill firefighting simulation induces similar physiological responses to those reported for live fire and simulated firefighting scenarios.
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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 | 0.000 |
| 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) | 0.001 | 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".