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Record W2003413141 · doi:10.1029/2006je002782

Mechanisms for cessation of magmatic resurfacing on Venus

2007· article· en· W2003413141 on OpenAlexfundno aff
C. C. Reese, V. S. Solomatov, C. P. Orth

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2007
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersMcGill University
KeywordsLithosphereMantle (geology)GeologyMantle convectionVenusConvectionGeophysicsPetrologyTransition zoneTectonicsAstrobiologyMechanicsSeismology

Abstract

fetched live from OpenAlex

Proposed mechanisms of resurfacing on Venus about 0.3–1 Gyr ago usually involve either some form of tectonic resurfacing in which Venusian lithosphere is recycled mechanically or magmatic resurfacing where essentially immobile lithosphere is covered by lava. The focus of this study is mechanisms of magmatic resurfacing in the stagnant lid regime of mantle convection. Parameterized convection models suggest that cessation of magmatic resurfacing can occur in several ways. (1) The mantle temperature drops sufficiently such that mantle rising adiabatically does not cross the solidus. (2) The molten layer migrates below the solid/melt density inversion at 250–500 km so that no melt can escape. (3) Sublithospheric small‐scale convection stops and conductive thickening of the lid suppresses melting. In each case, inability of magma to penetrate thickened Venusian lithosphere may play a role. The timing of melt cessation and duration of late stage resurfacing depend on various factors such as mantle rheology, degree of mantle depletion, and depth of resurfacing. The models indicate that the waning stages of resurfacing which result in surface age variations can last ∼0.1–1 Gyr. A general trend of recent lithospheric thickening is also predicted. Some cases exhibit a rapid transition from relatively thin to thick lid as suggested by previous authors.

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)0.002
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.204

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.048
GPT teacher head0.344
Teacher spread0.296 · 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 designTheoretical or conceptual
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

Citations41
Published2007
Admission routes1
Has abstractyes

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