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Record W3010326752

The influence of mantle internal heating on lithospheric mobility: implications for super-Earths

2013· article· en· W3010326752 on OpenAlexaff
Claudia Stein, J. P. Lowman, Ulrich Hansen

Bibliographic record

VenueEPSC · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicStellar, planetary, and galactic studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLithosphereMantle (geology)Mantle convectionInternal heatingConvectionGeophysicsPlanetGeologyPlate tectonicsRayleigh numberViscosityTectonicsMechanicsThermodynamicsPhysicsNatural convectionAstrophysicsSeismology
DOInot available

Abstract

fetched live from OpenAlex

Abstract Super-Earths, a recently discovered class of exoplanets, have been inferred to be of a similar rock and metal composition to the Earth. As a result, the possibility that they are characterised by the presence of plate tectonics has been widely debated. However, as the super-Earths have higher masses than Earth, it is assumed that they will also have higher Rayleigh numbers and non-dimensional heating rates. Accordingly, we conduct a systematic 2D study to investigate the influence of these parameters on the surface behaviour of mantle convection. The main focus of our work considers the response of surface motion to the mantle's internal heating. However, we also include an analysis of other parameters scaling with planet mass, such as viscosity. In agreement with the findings of Valencia and O'Connell (2009) and van Heck and Tackley (2011) we find plate-like surface mobilisation for increased Rayleigh numbers. But increasing the internal heating leads to the formation of a strong stagnant-lid because the mantle heating effects thermally activated viscosity. Additionally, viscosity is affected by the increased pressures and temperatures of super-Earths. In total, our findings indicate that surface mobility will likely be reduced on super-sized Earths. Our numerical models show that the interior temperature of the convecting system is of vital importance. In planets with a hotter interior plate tectonics is less likely.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.180

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)0.0000.000

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 head0.248
Teacher spread0.237 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2013
Admission routes1
Has abstractyes

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