Low frequency earthquakes below southern Vancouver Island
Bibliographic record
Abstract
The nature and distribution of low frequency earthquakes (LFEs) in subduction zones provide insight into plate boundary deformation downdip of the locked seismogenic zone. We employ network autocorrelation detection to identify LFE families beneath southern Vancouver Island and environs. An initial suite of 5775 LFEs detected in 2004 and 2005 at a select set of 7 stations is grouped into 140 families using waveform cluster analysis. These families are used as templates within an iterative network cross correlation scheme to detect LFEs across different tremor episodes, incorporate new stations, and improve LFE template signal‐to‐noise ratio. As in southwest Japan, representative LFE locations define a relatively tight, dipping surface several km above the locus of intraslab seismicity, within a prominent, dipping low‐velocity zone (LVZ). LFE polarizations for near‐vertical source‐receiver geometries possess a remarkably uniform dipolar signature indicative of point‐source, double‐couple excitation. Focal mechanisms determined fromP‐wave first motions are characterized by a combination of strike‐slip and thrust faulting. We suggest that LFEs and regular intraslab seismicity occur in distinct structural and stress regimes. The LVZ, inferred to represent weak, overpressured, porous and mylonitized metabasalts of oceanic crustal Layer 2, separates LFEs manifesting deformation within a plate boundary shear zone from intraslab earthquakes generated by tensional stresses and dehydration embrittlement within a more competent lower oceanic crustal Layer 3 and underlying mantle.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".