Exploring Seismic Hazard Scenarios of Potentially Active Faults in the Southern Coast Mountains of British Columbia, Canada
Bibliographic record
Abstract
ABSTRACT The southern Coast Mountains of British Columbia, Canada, lie landward of the northern Cascadia subduction zone margin. These mountains host an abundance of mapped faults, many of which are inherited from a complex deformational history. Geologic and geodetic evidence point to the possibility of some of these faults being active, posing a threat of future damaging earthquakes. However, the glacial history and slow deformation of the mountain belt impose challenges on identifying which faults are active. Although an in-depth investigation of all the faults is ideal, it is difficult to conduct due to the abundance of faults and the scale of the region. In this study, we quantified the potential impact of a selection of these faults to nearby population centers to gain insights on prioritization for further studies. We analyzed the seismic hazard curves of eight major potentially active faults and compared them with the seismic sources from the sixth-Generation Canadian Seismic Hazard model. We used hypothetical occurrence rates to reflect a range of possible values for Holocene-active faults. We then calculated the changes in the uniform-hazard spectra at a 2% probability of exceedance in 50 yr, relative to the reference model. The results indicate that source-to-site distance is the most influential factor for determining which faults contribute the most shaking intensity for a particular site. Furthermore, the increase in hazard relative to the reference model is greatest at long spectral periods, which affect taller buildings and structures. Our findings suggest that the Fraser fault, Britannia shear zone, Alouette Lake fault, and other candidate faults near Vancouver should be prioritized for future investigation. This analysis may be useful in other regions where shallow fault activity is in question, and prioritization is required to direct limited resources for study.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".