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Record W2079619446 · doi:10.1088/2041-8205/768/2/l30

THE EFFECT OF LOWER MANTLE METALLIZATION ON MAGNETIC FIELD GENERATION IN ROCKY EXOPLANETS

2013· article· en· W2079619446 on OpenAlexaff

Bibliographic record

VenueThe Astrophysical Journal Letters · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDynamoMantle (geology)ExoplanetMagnetic fieldCore–mantle boundaryDynamo theory

Abstract

fetched live from OpenAlex

Recent theoretical and experimental evidence indicates that many of the materials that are thought to exist in the mantles of terrestrial exoplanets will metallize and become good conductors of electricity at mantle pressures. This allows for strong electromagnetic coupling of the core and the mantle in these planets. We use a numerical dynamo model to study the effect of a metallized lower mantle on the dynamos of terrestrial exoplanets using several inner core sizes and mantle conductivities. We find that the addition of an electrically conducting mantle results in stronger core-mantle boundary fields because of the increase in magnetic field stretching. We also find that a metallized mantle destabilizes the dynamo resulting in less dipolar, less axisymmetric poloidal magnetic fields at the core-mantle boundary. The conducting mantle efficiently screens these fields to produce weaker surface fields. We conclude that a conducting mantle will make the detection of extrasolar terrestrial magnetic fields more difficult while making the magnetic fields in the dynamo region stronger.

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)0.001
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
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 head0.004
GPT teacher head0.196
Teacher spread0.192 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

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