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Record W2068465863 · doi:10.1029/2007gl031396

Effect of lower mantle viscosity on the time‐dependence of plate velocities in three‐dimensional mantle convection models

2007· article· en· W2068465863 on OpenAlexaff
Andrew Gait, J. P. Lowman

Bibliographic record

VenueGeophysical Research Letters · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsMantle convectionMantle (geology)GeologyGeophysicsConvectionViscosityEarth's internal heat budgetPlate tectonicsMechanicsThermodynamicsPhysicsLithosphereSeismology

Abstract

fetched live from OpenAlex

Earth's evolution has featured stages of relatively steady plate motion interrupted by brief periods of rapid change in plate direction. Previous studies have shown that vigorously convecting internally heated systems featuring dynamically determined plate‐like surface motion can also be characterized by predominantly steady periods punctuated by comparatively short reorganization events. Here, we investigate time‐dependence in two mantle convection models featuring significantly contrasting viscosity profiles and assess the influence of lower mantle viscosity on plate velocity time‐dependence. We model a system featuring nine finite thickness viscous plates at the top of a 6 × 6 × 1 Cartesian geometry solution domain. We find that plate reorganization events involving between 1 and 3 plates occur with geologically relevant frequency in a calculation featuring a factor of 36 increase in lower mantle viscosity relative to the upper mantle. Specifying a mantle viscosity at a depth of 2000 km that is 3000 times greater than the upper mantle viscosity suppresses this time‐dependence.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.271
Teacher spread0.248 · 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

Citations4
Published2007
Admission routes1
Has abstractyes

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