A Consistent Cross‐Border Seismic Hazard Methodology for Loss Estimation and Risk Management along the Border Regions of Canada and the United States
Bibliographic record
Abstract
We provide a methodology that seamlessly integrates national seismic hazard models across the Canada‐U.S. border to provide earthquake risk managers with updated and consistent seismic hazard science and technology in the two countries. Consistent with our U.S. hazard model, we developed a new Canadian model that incorporates (1) spatially varying seismicity for the major metropolitan areas of southeastern and southwestern Canada and the United States, (2) a comprehensive probabilistic model for the Cascadia subduction zone that includes M 8.0–9.2 interface earthquakes, (3) a consistent set of ground motion prediction equations across eastern and western North America, and (4) a soil‐based attenuation (SBA) methodology that mitigates uncertainty in the conversion of earthquake motions from rock to soil, on which the majority of exposure is located. NEHRP site conditions are mapped for all of Canada from existing geological data, and NEHRP site factors are used to account for local site conditions.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".