The effects of exercise-induced heat stress on cognitive function in firefighters
Bibliographic record
Abstract
Background. Firefighting requires tremendous cognitive demands including assessing emergency scenes, executing critical decisions, and situational awareness of their surroundings. The aim of this study was to determine the effects of differing rates of increasing core temperature on cognitive function during exercise-induced heat stress. Methods. Nineteen male firefighters were exposed to repeated cognitive assessments, randomized and counter-balanced, in 30°C and 35°C and 50% humidity. Participants performed treadmill walking (4.5 km . h -1 and 2.5% grade) with cognitive function assessed before exercise (PRE), after mounting the treadmill (Cog 1), at core temperatures of 37.8°C (Cog 2), 38.5°C (Cog 3), and 39.0°C (Cog 4), after dismounting the treadmill (POST), and following an active cooling recovery to a core temperature of 37.8°C (REC). The cognitive tests implemented at PRE and POST were spatial working memory (SWM), rapid visual information processing (RVP), and reaction time (RTI) while paired associates learning (PAL) and spatial span (SSP) were assessed at Cog 1, Cog 2, Cog 3, and Cog 4. All five cognitive tests were assessed at REC. Results. Planned contrasts revealed that SSP and PAL were impaired at Cog 3, with SSP also impaired at Cog 4 compared to Cog 1. REC revealed no difference compared to Cog 1, but increased errors compared to Cog 2 for PAL. Conclusions. The decrements in cognitive function observed at a core temperature of 38.5°C are likely attributed to the cognitive resources required to maintain performance being overloaded due to increasing task complexity and external stimuli from exercise-induced heat stress. The addition of an active cooling recovery restored cognitive function to initial levels.
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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".