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Record W3155750838 · doi:10.5194/egusphere-egu21-14473

Slow subduction initiation drives fast mantle upwelling and lithosphere formation 

2021· preprint· en· W3155750838 on OpenAlexaff
Mathieu Soret, Guillaume Bonnet, Philippe Agard, Kyle P. Larson, John M. Cottle, Benoît Dubacq, Andrew Kylander‐Clark, Mark Button, Nicolas Rividi

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsSubductionGeologyLithosphereMantle (geology)SlabPlate tectonicsEclogitizationSeismologyTectonicsGeophysicsOceanic crust

Abstract

fetched live from OpenAlex

Subduction zones are crucial features of Earth’s plate tectonics, yet subduction initiation remains enigmatic and controversial. Herein, we reappraise the timing of formation of the first fragments detached from the leading edge of the downgoing slab during subduction initiation (i.e., the Semail metamorphic sole; Oman–United Arab Emirates). Based on geochronology and phase equilibrium modeling, we demonstrate that subduction initiated prior to 105 Ma and at a slow pace (< cm/yr). Subduction stagnated at relatively warm conditions (15–20°C/km) for at least 10 Myr before evolving into a faster (≥ 2–5 cm/yr) and colder (~7°C/km) self-sustained regime. Subduction unlocking at 95-96 Ma, through the progressive change of the interplate thermo-mechanical structure, triggered the onset of slab retreat, large-scale corner flow and fast ocean spreading in the overriding plate. These results reconcile conflicting analogue and numerical subduction initiation models and reveal the thermal, mechanical and kinematic complexity of early subduction steps.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.019
GPT teacher head0.216
Teacher spread0.197 · 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
Published2021
Admission routes1
Has abstractyes

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