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Record W6974098827 · doi:10.57757/iugg23-2522

The next cascadia slab model

2023· article· en· W6974098827 on OpenAlexaff

Bibliographic record

VenuePublication Database GFZ (GFZ German Research Centre for Geosciences) · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of OttawaUniversity of British Columbia
Fundersnot available
KeywordsSubductionOceanic crustCrustSlabReceiver functionShear zoneConvergent boundary

Abstract

fetched live from OpenAlex

<!--!introduction!--> Detailed knowledge about the location and properties of the structures that host the megathrust is required to predict ground motions, model tsunami hazards and better understand subduction zone processes in Cascadia. Here we present our efforts to bring forward a new, detailed slab model based on azimuthally variable receiver functions from almost 300 on-shore 3-component broadband seismic stations. We observe a characteristic succession of a negative top-, a positive central- and the positive oceanic Moho-conversion, where either the top or central conversion may be absent. We interpret it as the subducting oceanic crust that is at places overlain by, or contained within, a low-velocity zone. Inverse modeling of synthetic receiver functions allows us to resolve the strike and dip of this structure, the interface depths and seismic velocities of the intervening material along the fore-arc. The top conversion exhibits a progressive landward evolution displaying (i) a weak contrast with overriding crust near the coast, (ii) full expression with the development of an upper low-velocity zone downdip, and (iii) disappearance in advance into the fore-arc, where the oceanic crust is inferred to turn to eclogite. The thickness of the entire structure frequently exceeds the thickness of the oceanic crust offshore. At depth, the location of the central converter approximately correlates with the location of low-frequency earthquakes. These observations suggest that the subduction megathrust either continues downdip, a few kilometers below the top conversion, or widens into a distributed shear zone that includes upper plate material.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.119
Threshold uncertainty score0.237

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.099
GPT teacher head0.344
Teacher spread0.245 · 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 designSimulation or modeling
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

Citations0
Published2023
Admission routes1
Has abstractyes

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