Low‐frequency earthquakes at the southern Cascadia margin
Bibliographic record
Abstract
Abstract We use seismic waveform data from the Mendocino Experiment to detect low‐frequency earthquakes (LFEs) beneath Northern California during the April 2008 tremor‐and‐slip episode. In southern Cascadia, 59 templates were generated using iterative network cross correlation and stacking and grouped into 34 distinct LFE families. The main front of tremor epicenters migrates along strike at 9 km d −1 ; we also find one instance of rapid tremor reversal, observed to propagate in the opposite direction at 10–20 km h −1 . As in other regions of Cascadia, LFE hypocenters from this study lie several kilometers above a recent plate interface model. South of Cascadia, LFEs were discovered on the Maacama and Bucknell Creek faults. The Bucknell Creek Fault may be the youngest fault yet observed to host LFEs. These fault zones also host shallow earthquake swarms with repeating events that are distinct from LFEs in their spectral and recurrence characteristics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".