Towards establishing evidence-based guidelines on maximum indoor temperatures during hot weather in temperate continental climates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Rising environmental temperatures represent a major threat to human health. The activation of heat advisories using evidence-based thresholds for high-risk outdoor ambient temperatures have been shown to be an effective strategy to save lives during hot weather. However, although the relationship between weather and human health has been widely defined by outdoor temperature, corresponding increases in indoor temperature during heat events can also be harmful to health especially in vulnerable populations. In this review, we discuss our current understanding of the relationship between outdoor temperature and human health and examine how human health can also be adversely influenced by high indoor temperatures during heat events. Our assessment of the existing literature revealed a high degree of variability in what can be considered an acceptable indoor temperature because there are differences in how different groups of people may respond physiologically and behaviorally to the same living environment. Finally, we demonstrate that both non-physiological (e.g., geographical location, urban density, building design) and physiological (e.g., sex, age, fitness, state of health) factors must be considered when defining an indoor temperature threshold for preserving human health in a warming global climate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 it