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Stresses induced in continental lithospheres by axisymmetric spherical convection

2004· article· en· W2145651782 on OpenAlexaff
S. L. Butler, Gary T. Jarvis

Bibliographic record

VenueGeophysical Journal International · 2004
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsYork UniversityUniversity of Saskatchewan
Fundersnot available
KeywordsGeologyMantle (geology)Mantle convectionMechanicsGeophysicsConvectionContinental marginPlate tectonicsSubductionGeometryPhysicsSeismologyTectonics

Abstract

fetched live from OpenAlex

We employ an axisymmetric spherical shell model of mantle convection to examine the magnitude of deviatoric tensile stresses generated in a stationary continental plate resulting from the subduction of oceanic plate material below an active continental margin. The model includes depth-dependent physical properties, uniform internal heating, compressibility and mineral phase-change boundaries at depths of 400 and 660 km. Below 100 km, mantle viscosity is assumed constant. Above 100 km, plate-like behavior may be approximated in axisymmetric spherical geometry by imposing (i) a factor of 10 viscosity contrast between the upper 100 km and the underlying mantle and (ii) a small variation of surface velocity within each plate such that plate mass is conserved and significant vertical mass flux at the base of the plates is therefore confined to the near vicinity of the plate boundaries. We find surface stresses generated by counterflow under our model continental margins is insufficient to actively rift a supercontinent in all but one case. Earth-like curvature appears to be a major factor in reducing surface stresses relative to those found previously in constant viscosity models in plane layer geometry. A simple internal loading model allows us to estimate this effect as a 20 per cent average reduction in stress generation. This suggests that continental rifting requires the pre-existence of localized zones of weakness.

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 score0.452
Threshold uncertainty score0.999

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)0.0020.000

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 head0.009
GPT teacher head0.225
Teacher spread0.217 · 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

Citations16
Published2004
Admission routes1
Has abstractyes

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