Occupational heat stress management: Does one size fit all?
Bibliographic record
Abstract
Heat stress is a deadly occupational hazard that is projected to increase in severity with global warming. While upper limits for heat stress designed to protect all workers have been recommended by occupational safety institutes for some time, heat stress continues to compromise health and productivity. In our view, this is largely explained by the inability of existing guidelines to consider the inter-individual (age, sex, disease, others) and intra-individual (medication use, fitness, hydration, others) factors that cause extensive variability in physiological tolerance to a given heat stress. In conditions that do not exceed the recommended limits, this 'one size fits all' approach to heat stress management can lead to reductions in productivity in more heat-tolerant workers, while compromising safety in less heat-tolerant workers who may develop heat-related illness, even in temperate conditions. Herein, we discuss future directions in occupational heat stress management that consider this individual variability.
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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 | 0.010 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".