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Record W3034680366 · doi:10.1029/2020je006396

A Past Lunar Dynamo Thermally Driven by the Precession of Its Inner Core

2020· article· en· W3034680366 on OpenAlexafffund
Christopher Stys, Mathieu Dumberry

Bibliographic record

VenueJournal of Geophysical Research Planets · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of Alberta
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
KeywordsDynamoPrecessionInner coreCore (optical fiber)Dynamo theoryAstrobiologyPhysicsGeophysicsGeologyGeodesyAstronomyMagnetic fieldOptics

Abstract

fetched live from OpenAlex

Abstract The Cassini state equilibrium associated with the precession of the Moon predicts that the mantle, fluid core, and solid inner core precess at different angles. We present estimates of the dissipation from viscous friction associated with the differential precession at the core‐mantle boundary (CMB), Q c m b , and at the inner core boundary (ICB), Q i c b , as a function of the evolving lunar orbit. We focus on the latter and show that, provided the inner core was larger than 100 km, Q i c b may have been as high as 10 10 –10 11 W for most of the lunar history for a broad range of core density models. This is larger than the power required to maintain the fluid core in an adiabatic state; therefore, the heat released by the differential precession at the ICB can drive a past lunar dynamo by thermal convection. This dynamo can outlive the dynamo from precession at the CMB and may have shut off only relatively recently. Estimates of the magnetic field strength at the lunar surface are of the order of a few μT, compatible with the lunar paleomagnetic intensities recorded after 3 Ga. We further show that it is possible that a transition of the Cassini state associated with the inner core may have occurred as a result of the evolution of the lunar orbit. The heat flux associated with Q i c b can be of the order of a few mW m −2 , which should slow down inner core growth and be included in thermal evolution models of the lunar core.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.514
Threshold uncertainty score0.253

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 integrity0.0000.001
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 head0.059
GPT teacher head0.334
Teacher spread0.275 · 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 designBench or experimental
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

Citations23
Published2020
Admission routes2
Has abstractyes

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