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Record W4380791981 · doi:10.1029/2022jb025486

Focusing Effects of Teleseismic Wavefields by the Subducting Plate Beneath Cascadia

2023· article· en· W4380791981 on OpenAlexaboutno aff
Guanning Pang, G. A. Abers, Peter E. van Keken

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsGeologySubductionSeismologyAmplitudeSlabAttenuationAzimuthSeismic waveBroadbandScatteringGeophysicsTectonicsPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract Seismic wave amplitudes have tremendous sensitivity to subduction structure; however, they are affected by attenuation, scattering and focusing, and have therefore been sparsely used compared with traveltimes. We measure and model teleseismic body wave amplitudes recorded at a dense broadband array in the Washington Cascades. These data show anomalous amplitude variations with complex azimuthal dependence at frequencies as low as 0.05 Hz, accompanied by significant multipathing. We demonstrate using spectral‐element numerical simulations that focusing of the teleseismic wavefield by the Juan de Fuca slab is responsible for some of the amplitude anomalies. The focusing effects can contaminate the apparent differential attenuation measurements and produce at least 20% of the inferred attenuation signal. Our results indicate that the amplitudes are sensitive to the subducting slab geometry and subduction structure, and can be used to refine seismic images. Ubiquitous and consistent amplitude anomalies are observed along the arc, suggesting that the Juan de Fuca slab may be continuous from Canada to northern California.

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 score0.087
Threshold uncertainty score0.173

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.030
GPT teacher head0.309
Teacher spread0.280 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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