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Record W1604312882 · doi:10.1002/2014jb011744

Self‐similar rupture implied by scaling properties of volcanic earthquakes occurring during the 2004‐2008 eruption of Mount St. Helens, Washington

2015· article· en· W1604312882 on OpenAlexaff
R. M. Harrington, Grzegorz Kwiatek, S. C. Moran

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2015
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsSeismologyVolcanoScalingGeologyImpact craterSeismometerGeodesyPhysicsMathematicsGeometry

Abstract

fetched live from OpenAlex

Abstract We analyze a group of 6073 low‐frequency earthquakes recorded during a week‐long temporary deployment of broadband seismometers at distances of less than 3 km from the crater at Mount St. Helens in September of 2006. We estimate the seismic moment (M0) and spectral corner frequency (f0) using a spectral ratio approach for events with a high signal‐to‐noise (SNR) ratio that have a cross‐correlation coefficient of 0.8 or greater with at least five other events. A cluster analysis of cross‐correlation values indicates that the group of 421 events meeting the SNR and cross‐correlation criteria forms eight event families that exhibit largely self‐similar scaling. We estimate the M0 and f0 values of the 421 events and calculate their static stress drop and scaled energy (ER/M0) values. The estimated values suggest self‐similar scaling within families, as well as between five of eight families (i.e., and constant). We speculate that differences in scaled energy values for the two families with variable scaling may result from a lack of resolution in the velocity model. The observation of self‐similar scaling is the first of its kind for such a large group of low‐frequency volcanic tectonic events occurring during a single active dome extrusion eruption.

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)0.002
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.000
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 head0.044
GPT teacher head0.286
Teacher spread0.243 · 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

Citations24
Published2015
Admission routes1
Has abstractyes

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