Earthquake rupture through a step-over fault system: A case study of the Leech River Fault, southern Vancouver Island
Bibliographic record
Abstract
The Leech River fault (LRF) zone located on the southern Vancouver Island can be interpreted as an extensional step-over system based on geological mapping and microseismicity relocation. It consists of two sub-parallel right-lateral active fault structures: the primary NNE dipping LRF structure to the north, and a secondary sub-vertical structure to the south, possibly an extension of the Southern Whidbey Island fault (SWIF). The possibility of an earthquake rupture nucleated on the LRF jumping across the step-over and continuing propagation on the SWIF has significant implications for seismic hazard of the populated southern Vancouver area. To study earthquake rupture jumping scenarios across the LRF system, we develop a finite-element model to simulate dynamic ruptures governed by a linear slip-weakening frictional law. The stress perturbations radiated from the LRF rupture will induce an Over Stressed Zone (OSZ, where shear stress exceeds static frictional strength) on the SWIF. With the increase of the OSZ size R_e, rupture develops from stopping on LRF (no jumping), to breaking part of the SWIF (self-arresting) or the entire SWIF (break-away). We demonstrate that rupture jumping scenario is a collective result depending on a range of parameters. Target parameters in our study include fault initial stress level, step-over offset distance and fault burial depth. We find that R_e and the receiver fault stress status are the keystone variables directly controlling rupture jumping scenarios, while other parameters exert their influence by resulting in different R_e.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".