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Record W2107466955 · doi:10.1785/0120100225

Regional Spectral Analysis of Three Moderate Earthquakes in Northeastern North America

2011· article· en· W2107466955 on OpenAlexaboutno aff
John Boatwright, Linda C. Seekins

Bibliographic record

VenueBulletin of the Seismological Society of America · 2011
Typearticle
Languageen
FieldEngineering
TopicSeismic Performance and Analysis
Canadian institutionsnot available
FundersNational Centre for Biological Sciences
KeywordsSeismologyGeologySpectral analysisPhysics

Abstract

fetched live from OpenAlex

Abstract We analyze Fourier spectra obtained from the horizontal components of broadband and accelerogram data from the 1997 Cap-Rouge, the 2002 Ausable Forks, and the 2005 Riviere-du-Loup earthquakes, recorded by Canadian and American stations sited on rock at hypocentral distances from 23 to 602 km. We check the recorded spectra closely for anomalies that might result from site resonance or source effects. We use Beresnev and Atkinson’s (1997) near-surface velocity structures and Boore and Joyner’s (1997) quarter-wave method to estimate site response at hard- and soft-rock sites. We revise the Street et al. (1975) model for geometrical spreading, adopting a crossover distance of r o =50 km instead of 100 km. We obtain an average attenuation of Q =410±25 f 0.50±0.03 for S + L g +surface waves with ray paths in the Appalachian and southeastern Grenville Provinces. We correct the recorded spectra for attenuation and site response to estimate source spectral shape and radiated energy for these three earthquakes and the 1988 M  5.8 Saguenay earthquake. The Brune stress drops range from 130 to 419 bars, and the apparent stresses range from 39 to 63 bars. The corrected source spectral shapes of these earthquakes are somewhat variable for frequencies from 0.2 to 2 Hz, falling slightly below the fitted Brune spectra.

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 score0.058
Threshold uncertainty score0.116

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 science0.0000.000
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 head0.023
GPT teacher head0.199
Teacher spread0.177 · 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

Citations51
Published2011
Admission routes1
Has abstractyes

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