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Record W2513355907 · doi:10.1002/2016gl069755

Tectonic tremor on Vancouver Island, Cascadia, modulated by the body and surface waves of the <i>M<sub>w</sub></i> 8.6 and 8.2, 2012 East Indian Ocean earthquakes

2016· article· en· W2513355907 on OpenAlexaboutno aff
Bhaskar Kundu, Abhijit Ghosh, Manuel M. Mendoza, Roland Bürgmann, Vineet K. Gahalaut, Dipankar Saikia

Bibliographic record

VenueGeophysical Research Letters · 2016
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsnot available
Fundersnot available
KeywordsSeismologyGeologySubductionTectonicsEpisodic tremor and slipTsunami waveSlip (aerodynamics)Plate tectonicsSeismic waveIndian oceanSurface waveModulation (music)OceanographyPhysics

Abstract

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Abstract The 2012 East Indian Ocean earthquake (Mw 8.6), so far the largest intraoceanic plate strike‐slip event ever recorded, modulated tectonic tremors in the Cascadia subduction zone. The rate of tremor activity near Vancouver Island increased by about 1.5 times from its background level during the passage of seismic waves of this earthquake. In most cases of dynamic modulation, large‐amplitude and long‐period surface waves stimulate tremors. However, in this case even the small stress change caused by body waves generated by the 2012 earthquake modulated tremor activity. The tremor modulation continued during the passage of the surface waves, subsequent to which the tremor activity returned to background rates. Similar tremor modulation is observed during the passage of the teleseismic waves from the Mw 8.2 event, which occurs about 2 h later near the Mw 8.6 event. We show that dynamic stresses from back‐to‐back large teleseismic events can strongly influence tremor sources.

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)0.000
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 score0.514
Threshold uncertainty score0.967

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.013
GPT teacher head0.224
Teacher spread0.210 · 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

Citations14
Published2016
Admission routes1
Has abstractyes

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