Spatial Distribution of Tremor Episodes From Long‐Term Monitoring in the Northern Cascadia Subduction Zone
Bibliographic record
Abstract
Abstract Large bursts of non‐volcanic tremor (“major” tremor episodes) correlated with geodetic deformation recur regularly in the Cascadia subduction zone and are often called episodic tremor and slip (ETS). Minor episodes of tremor between ETS are ubiquitous but have been understudied. This paper assesses time‐invariant characteristics of tremor episodes of all sizes within northern Cascadia. We derive a catalog of tremor episodes ranging in size from 10 to >13,000 tremor events using the results of 17 years of tremor monitoring. Minor episodes represent ∼96% of all 896 tremor episodes and their occurrence varies on 10‐km scales. Using estimates for the depth of the forearc Moho and subducting slab, we observe an association between the location of the forearc mantle corner (FMC) and tremor occurrence that leads to along‐dip modality. Bimodality, present in southern Washington and Vancouver Island, represents the segmentation of major and minor episodes up‐dip and down‐dip of the FMC, respectively. Unimodality, present in Puget Sound, results when the FMC is located near the down‐dip edge of the ETS zone and no segmentation occurs. We also use our extensive tremor episode catalog alongside three‐dimensional regional tomographic velocity models to reassess the relationship between tremor activity and low Vp/Vs signatures in the forearc. We do not find a correlation between tremor episode recurrence intervals and Vp/Vs, contrary to some previous work, suggesting that controls on silica precipitation in the forearc crust are not dominant controls of tremor episode recurrence, or that the association is not widely observable.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".