Bibliographic record
Abstract
Abstract A catalog of low frequency events (LFEs) beneath Vancouver Island is analyzed in the context of a granular flow model. The catalog contains origin‐times and magnitudes of 269,423 LFEs grouped within 130 families and recorded between 2003 and 2013. Each family represents a distinct location within the boundary between the subducting Juan de Fuca and overriding North American plates. The LFEs occurred during 10 episodic tremor and slip (ETS) events that recurred at ∼14‐month intervals and lasted for about a week. With one exception, each family was active in all 10 ETS episodes. Our analysis suggests that LFEs do not follow Gutenberg‐Richter statistics, but are normally distributed with respect to magnitude and, therefore, log‐normally distributed with respect to moment. The Kostrov strain associated with the moments in a given family is used to estimate its size as L = 350 ± 15 m. These observations are explained through a model of granular flow in a channel that accommodates displacement along the plate boundary. In this model the LFE families correspond to granular jams in flow that persist over many ETS episodes. Each LFE is a slip between two grains in the jam. The log‐normal distribution of LFE moments can be ascribed to a theoretically predicted log‐normal distribution of grain sizes in each jam. This model explains the weak dependence of seismic duration on LFE moment because frictional slip between grains in an over‐pressured environment need not scale like a growing rupture in an elastic medium.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".