A comparative analysis of approaches to expanding Canada’s Earthquake Scenario Catalogue
Bibliographic record
Abstract
Canada’s earthquake scenario catalogue is a nation-wide collection of possible earthquake rupture scenarios that allows us to understand which populations and assets will be impacted by the rupture of particular faults (or their segments). In the past, scenarios were often generated on an ad hoc basis, when they were needed by practitioners. As new information from geologic, geomorphic, geophysical, and geodetic studies become available, it is possible to model additional earthquake rupture scenarios for inclusion in Canada’s earthquake scenario catalogue, which will be crucial to providing relevant seismic hazard and risk estimates to end users such as community planners and emergency managers. This is especially valuable in the seismically active intraplate regions of eastern Canada, where the seismic risk awareness, perception and, consequently, preparedness, is relatively low. In updating this catalogue, we employed different approaches to modelling earthquake hazard and risk scenarios using the Global Earthquake Model Foundation’s (GEM) OpenQuake Engine. We conducted a ‘known events’ approach, which involved modelling representative events for historical earthquakes and potentially active faults. We also implemented a ‘systematic risk-based’ approach, which involved disaggregating the seismic risk at certain locations into the relative contributions from different seismic source zones, and ranking the seismic risk for each census subdivision (approximately aligned with municipalities) across Canada. The goal of the ‘systematic risk-based’ approach was to mitigate the irregular coverage of the existing catalogue. We compare the nature of the two catalogues for one community, taking into account the ways these kinds of catalogues are used in Canada and elsewhere. Finally, we described the overall spatial variations in seismic risk, focusing on regions where seismic zones are close to densely-populated areas, such as the offshore BC region and Cascadia subduction zone in western Canada; and the Western Quebec, Charlevoix, lower St. Lawrence, and southern Great Lakes seismic zones in eastern Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.016 | 0.022 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".