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Record W2030087806 · doi:10.1186/bf03352385

Tomographic image of low P velocity anomalies above slab in northern Cascadia subduction zone

2014· article· en· W2030087806 on OpenAlexaffabout
Dapeng Zhao, Kelin Wang, Garry C. Rogers, Simon M. Peacock

Bibliographic record

VenueEarth Planets and Space · 2014
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsGeological Survey of Canada
FundersUniversity of Washington
KeywordsGeologySubductionSeismologySeismic tomographySlabSlab windowOceanic crustTomographyCrustMantle (geology)EclogiteConvergent boundaryGeophysicsTectonics

Abstract

fetched live from OpenAlex

At the Cascadia margin the Juan de Fuca plate is subducting beneath the North America plate, causing active seismicity within both plates. Earthquakes occur down to a maximum depth of 80 km within the descending oceanic plate and to about 30 km in the overriding continental plate. We use a method of seismic tomography to invert 28,230 P wave arrival times from 2666 local earthquakes that occurred in and around Vancouver Island from 1970 to 1990. The tomography model uses about 30 km horizontal and 12–19 km vertical grid spacing and assumes that the seismic velocity perturbations vary continuously between grid points. Velocity structures can be obtained to a depth of 65 km. The obtained tomographic image shows an extensive low velocity zone above the subducted slab at about 45 km depth and patches of low velocities at shallower depths just seaward of the volcanic front. The deeper extensive low velocity zone may indicate the presence of partially hydrated mantle, most likely serpentinite, as a result of slab dehydration associated with the transformation of metabasalt to eclogite. One of the shallow low velocity patches coincides with an abrupt increase in surface heat flow and may reflect the presence of partial melts or water in the crust.

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 score0.113
Threshold uncertainty score0.224

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.005
GPT teacher head0.179
Teacher spread0.174 · 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

Citations72
Published2014
Admission routes2
Has abstractyes

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