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Record W1696170708 · doi:10.1029/2009gl041417

Giant impact stratification of the Martian core

2010· article· en· W1696170708 on OpenAlexafffund
Jafar Arkani‐Hamed, Peter Olson

Bibliographic record

VenueGeophysical Research Letters · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsStratification (seeds)DynamoMartianMars Exploration ProgramGeologyShock waveThermal stratificationInner coreGeophysicsMantle (geology)Atmospheric sciencesMechanicsAstrobiologyPhysicsClimatologyMagnetic field

Abstract

fetched live from OpenAlex

We investigate the direct thermal effects of giant impacts on the Martian core and its dynamo. Shock wave heating of Mars is calculated in terms of the impact velocity and the final basin size. Although much of the shock wave heat is deposited in the mantle, shock heating from a giant impact produces non‐uniform temperatures in the core, leading to an overturn event and stable thermal stratification in the liquid core. Numerical dynamos with core heating from polar and equatorial impacts show that the overturn and stratification quickly destroys a pre‐existing core dynamo, within ten thousand years. Energy considerations reveal that both the stratification and the time required for removal of the stratification increase with impact size. Our calculations indicate that several tens to over one hundred million years are required for removal of core stratification following a giant impact.

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 score0.006
Threshold uncertainty score0.011

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 science0.0000.001
Research integrity0.0000.000
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 head0.045
GPT teacher head0.331
Teacher spread0.286 · 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

Citations37
Published2010
Admission routes2
Has abstractyes

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