A novel method for quantifying risks to climate change events using conditional value at risk: a multi-unit residential building case study in London, Ontario
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
Climate change may lead to more frequent and severe weather events, resulting in significant financial and human health impacts. This paper develops a risk metric using building performance simulation by associating thermal and incidental risks in buildings during power outages while considering multiple cold and hot events. Conditional Value at Risk (CVaR) is calculated using variations in outage events. According to the results, employing an integrated building design and a microgrid with photovoltaic panels that can be disconnected from the grid halves vulnerability related to ice storms and completely mitigates it for historical heatwave events. The variability study has revealed that a code-minimum design has eight times the CVaR of the as-built design. This novel methodology has the potential to inform future environmental, social, and corporate governance strategies and assist infrastructure operators in managing their risk exposure to future climate change events, considering various types of risks and multiple hazards.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it