Physical Work Limits for Toronto Firefighters in Warm Environments
Bibliographic record
Abstract
This study examined the relationship between time to reach critical end points (tolerance time [TT] and metabolic rate for three different environmental temperatures (25 degrees C, 30 degrees C, and 35 degrees C, 50% relative humidity), while wearing firefighting protective clothing (FPC) and self-contained breathing apparatus (SCBA). Thirty-seven Toronto firefighters (33 male and 4 female) were divided into four work groups defined as Heavy (H, n = 9), Moderate (M, n = 9), Light (L, n = 10), and Very Light (VL, n = 9). At 25 degrees C, 30 degrees C, and 35 degrees C, TT (min) decreased from 56 to 47 to 41 for H, 92 to 65 to 54 for M, 134 to 77 to 67 for L, and 196 to 121 to 87 for VL. Significant differences in TT were observed across all group comparisons, excluding M versus L at 30 degrees C and 35 degrees C, and H versus M at 35 degrees C. Comparing 25 degrees C to 30 degrees C, M, L, and VL had significant decreases in TT, whereas only VL had a significant decrease when 30 degrees C was compared to 35 degrees C. For 25 degrees C to 30 degrees C, the relative change in TT was significantly greater for L (37%) and VL (41%) compared with H (16%) and M (26%). For 30 degrees C to 35 degrees C, the relative change among the groups was similar and approximately 17%. During passive recovery at 35 degrees C, rectal temperature (T(re)) continued to increase 0.5 degrees C above T(re final), whereas heart rate declined significantly. These findings show the differential impact of environmental conditions at various metabolic rates on TT while wearing FPC and SCBA. Furthermore, these findings reveal passive recovery may not be sufficient to reduce T(re) below pre-recovery levels when working at higher metabolic rates in hot environments.
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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 | 0.001 | 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) | 0.001 | 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".