Using numerical modelling to investigate the driving forces of permanent forearc deformation in northern Cascadia
Bibliographic record
Abstract
We use boundary element method modelling to investigate whether subduction zone coupling drives permanent forearc deformation in the northern Cascadia subduction zone. Recent work in this region shows that several active crustal faults accommodate permanent strain north of the Olympic Peninsula in Washington State, USA and British Columbia, Canada. These faults are similar in that they strike west-northwest, have oblique right-lateral slip senses, and have low slip rates (<1 mm/yr). Paleoseismic studies show that despite the region’s low permanent strain rates, these faults have produced large (~M 7) earthquakes. Therefore understanding how and why these structures accommodate permanent deformation is crucial to assessing regional seismic hazard. Previous work has hypothesized this type of permanent forearc deformation may be driven by stress resulting from interseismic subduction zone coupling. To test this hypothesis, we used a 3D boundary element method model to determine whether coupling-driven forearc deformation can account for the observed right-lateral fault slip on one of the recently studied structures, the Leech River--Devils Mountain fault. Our model predicts left-lateral slip on this fault if strain results from subduction zone coupling alone, inconsistent with the observed kinematics. Additionally, if we use our model to mimic strain partitioning, where only strain resulting from the strike-slip component of subduction zone coupling is accommodated in the forearc, the predicted fault slip is also inconsistent with observations of fault kinematics. These simplified models represent a first-order test that contradicts the hypothesis that subduction zone coupling is the primary driver of permanent forearc deformation in northern Cascadia.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".