Portfolio Seismic Loss Estimation and Risk‐based Critical Scenarios for Residential Wooden Houses in Victoria, British Columbia, and Canada
Bibliographic record
Abstract
This study presents a city-wide seismic risk assessment of single-family wooden houses in Victoria, British Columbia, and Canada. The novelty and uniqueness of this study include considerations of detailed building-by-building exposure model for residential houses, current national seismic hazard model for Canada, and rigorous seismic fragility modeling of wooden houses based on nonlinear dynamic analysis of structures subjected to mainshock-aftershock sequences. A full consideration of stochastic event scenarios in probabilistic seismic risk analysis allows the identification of critical scenarios from overall regional seismic risk perspectives and provides valuable insights in informing earthquake disaster risk management actions. Outputs from the developed catastrophe model for Victoria are compared with the empirical model that was developed based on insurance claim data from the 1994 Northridge earthquake. Results of the seismic loss calculations highlight the importance of seismic resistance of the existing houses and of aftershock effects. The integrated use of the outputs from the advanced catastrophe model facilitates risk-based identification of critical earthquake scenarios, which are useful for different stakeholders for earthquake risk management purposes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".