An update on the seismic categorization for seismic risk assessment of existing Canadian buildings
Bibliographic record
Abstract
An investigation has been done to update key input parameters in the recent seismic-risk-screening tools developed by the National Research Council Canada for the six seismic categories. In this study, the seismic categorization system in the recent seismic-risk-screening tools of the National Research Council Canada is extended to include Canadian buildings abroad by including threshold peak ground acceleration values, a more global set of modified Mercalli intensity, peak ground acceleration, and spectral response acceleration and peak ground acceleration relationships. The relationships among spectral response acceleration, peak ground acceleration, and peak ground velocity values have been derived using least-squares regression analyses to obtain the threshold values of both peak values associated with various modified Mercalli intensity values for each seismic category. Based on the updated relationships, the seismic categorization system is applied to 679 locations in Canada and 226 locations outside Canada.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".