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Record W2592482134 · doi:10.1002/9781118944998.ch5

Geodynamical Models for Continental Delamination and Ocean Lithosphere Peel Away in an Orogenic Setting

2017· other· en· W2592482134 on OpenAlexafffund
Oğuz H. Göğüş, R. N. Pysklywec, Claudio Faccenna

Bibliographic record

VenueGeophysical monograph · 2017
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaTürkiye Bilimsel ve Teknolojik Araştırma KurumuDalhousie University
KeywordsGeologyLithosphereSubductionMantle (geology)Delamination (geology)GeophysicsPlate tectonicsOcean surface topographyCollision zoneAsthenosphereSeismologyTectonicsGeodesy

Abstract

fetched live from OpenAlex

This chapter presents numerical and laboratory-based geodynamical models that explore the evolution of the lithospheric delamination-peel-away process. The numerical model results are used to approximate the surface subsidence-uplift and crustal deformation patterns along a north-south cross section through East Anatolia, orthogonal to the Arabia-Eurasia plate boundary. Numerical model predictions show that the lithospheric delamination is associated with broad surface uplift as a result of mantle upwelling, controlled by thermal and isostatic effects. The chapter uses SOPALE, a plane strain, incompressible numerical code to study the thermomechanical behaviour of the coupled crust and mantle. It explores the evolution of the orogenic cycle from subduction to continental delamination. The chapter helps us to test the influence of varying plate convergence forcing along the model boundary during the subduction-delamination process and determine how surface topography evolves in this process.

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: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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

Citations10
Published2017
Admission routes2
Has abstractyes

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