MétaCan
Menu
← Back to cohort
Record W4401835717 · doi:10.31223/x5j98h

The Origin of Forearc Depressions

2024· preprint· en· W4401835717 on OpenAlexafffund
Chuqiao Huang, Shahin E. Dashtgard, H. Daniel Gibson, Andrew T. Calvert

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsForearcGeologySeismologySubductionTectonics

Abstract

fetched live from OpenAlex

Forearc depressions form over continental subduction zones with young, slowly subducting slabs and thick trench fills. They are bound seaward by a coast range and landward by a volcanic arc such that subsidence in forearc depressions occurs between orogens and in areas characterized by plate convergence. We propose a model for forearc depression formation based on geophysical and seismic data from four circum-Pacific subduction zones. Coast range crests coincide with >100 mGal gravity anomalies, which are attributed to underplated material and indicate that underplating drives coast range uplift. Coast range crests are situated near the down-dip termini of megathrust earthquake rupture zones, showing that coast ranges overlie where subduction interface sliding behaviour transitions from frictional to semi-frictional. This transition causes subduction interface shear stress to begin decreasing with depth and triggers underplating as shear stress becomes insufficient to drag buoyant material deeper. Forearc depressions are situated landward of inter-plate seismic phenomena, indicating they overlie the hydrated forearc mantle. Forearc depressions form as counter-flexural basins over the hydrated forearc mantle; in this position the upper plate crust is not supported by the flexurally rigid slab and can bend downwards. Forearc depressions do not form over old slabs because old slabs do not exceed the temperature threshold for semi-frictional sliding prior to intersecting the mantle wedge corner. Fast convergence rates and thin trench fills promote subduction erosion along the subduction interface, thereby prohibiting the formation of coast ranges, and by extension, forearc depressions.

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 score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.033
GPT teacher head0.346
Teacher spread0.313 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

Explore more

Same topicPsychosomatic Disorders and Their Treatments→French-language works237,207→