Development of assessment criteria for overheating risk analysis in buildings
Bibliographic record
Abstract
Overheating in buildings arising from global warming and extreme heat events (EHEs) is a growing health concern in urban areas of many countries. Overheating is the condition of the indoor environment that results in thermal discomfort or heat-related health stress to building occupants. Overheating is found in naturally ventilated buildings, buildings with limited cooling capacity or intermittent use of air conditioning, and buildings that experience extended periods of power outages or HVAC failure. Despite the extensive studies on this topic, there is a lack of a standard approach to analyse the overheating risk. This paper develops a framework to analyse the risk of overheating in buildings from the perspective of comfort and health of occupants through the use of building simulation. The framework includes four steps: (1) Generation of reference climate data for the historical period and future projections to extract various types of EHEs; (2) Development of heat stress metric to quantity the effect of heat on the comfort and health of occupants; (3) Generation of reference summer weather years for building simulation; and (4) Development of assessment criteria for overheating risk.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".