Regional seismic risk in British Columbia — classification of buildings and development of damage probability functions
Bibliographic record
Abstract
Regional seismic risk estimations are needed in southwestern British Columbia, since it is one of the most seismically active and highly populated regions in Canada. Regional estimations typically involve a large number of buildings, which makes it necessary to establish a building classification system, where the average response to earthquake shaking is assumed to be similar within each building class. In this study, buildings in British Columbia were divided into 31 classes based on their material, lateral load bearing system, height, use, and age. A damage probability matrix (DPM) was then developed for each building class which describes the probability of being in a certain damage level (i.e., light, moderate, heavy, etc.) given the ground shaking intensity. Next, a probability distribution function was fit to the discrete probability values at each intensity level. The products of this study, the building classification system, the DPMs, and the probability distribution functions will allow regional damage and loss estimations in the area.Key words: seismic risk, vulnerability, building classification, structural system, building response, damage, probability.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| 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".