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Record W4221040421 · doi:10.31223/x56623

Rapid tremor migration during few minute-long slow earthquakes in Cascadia

2022· preprint· en· W4221040421 on OpenAlexaboutno aff
Baptiste Gombert, J. C. Hawthorne

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
FundersNatural Environment Research Council
KeywordsSeismologyEpisodic tremor and slipGeologySlip (aerodynamics)Coherence (philosophical gambling strategy)SubductionGeodesyTectonicsPhysics

Abstract

fetched live from OpenAlex

Slow earthquakes are now commonly found to display a wide range of durations, moments, and slip and propagation speeds. But not all types of slow earthquakes have been examined in detail. Here we probe tremor bursts with durations between 1 and 30 minutes, which are likely driven by few minute-long bursts of aseismic slip. We use a coherence based technique to detect thousands of tremor bursts beneath Vancouver Island in Cascadia. Then we examine 17 of the ruptures by tracking their evolving tremor locations over an 8-km region. We find that tremor migrates at rates of 3 to 25 m/s: faster than longer tremor bursts . Though some observational biases persist, the short events’ speeds appear to fill a gap in the spectrum of observed slow earthquakes. They may provide further evidence that whatever fault zone process creates slow earthquakes, it must allow for faster slip and propagation in smaller ruptures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.968
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.025
GPT teacher head0.222
Teacher spread0.197 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2022
Admission routes1
Has abstractyes

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