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Record W3158343446 · doi:10.1130/g48803.1

How Himalayan collision stems from subduction

2021· article· en· W3158343446 on OpenAlexaff
Mathieu Soret, Kyle P. Larson, John M. Cottle, Asghar Ali

Bibliographic record

VenueGeology · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsGeologySubductionContinental collisionUnderplatingMetamorphic rockEclogiteContinental crustMetamorphic faciesGeochemistryBlueschistAccretionary wedgeOphioliteForeland basinContinental marginTerranePetrologyCrustSeismologyGeomorphologyTectonicsFaciesStructural basin

Abstract

fetched live from OpenAlex

Abstract The mechanisms and processes active during the transition from continental subduction to continental collision at the plate interface are largely unknown. Rock records of this transition are scarce, either not exposed or obliterated during subsequent events. We examine the tectono-metamorphic history of Barrovian metamorphic rocks from the western Himalayan orogenic wedge. We demonstrate that these rocks were buried to amphibolite-facies conditions from ≤47 Ma to 39 ± 1 Ma, synchronously with the formation (46 Ma) and partial exhumation (45–40 Ma) of the ultrahigh-pressure eclogites. This association indicates that convergence during continental subduction was accommodated via development of a deep orogenic wedge built through successive underplating of continental material, including the partially exhumed eclogites, likely in response to an increase in interplate coupling. This process resulted in the heating of the subduction interface (from ~7 to ~20 °C/km) through advective and/or conductive heat transfer. Rapid cooling of the wedge from 38 Ma, coeval with the formation of a foreland basin, are interpreted to result from indentation of a promontory of thick Indian 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.093
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0170.000

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 head0.012
GPT teacher head0.174
Teacher spread0.162 · 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 teacher head, not a consensus.

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

Citations40
Published2021
Admission routes1
Has abstractyes

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