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Record W4310679616 · doi:10.3390/cryst12121752

Thermal Convection in Vesta’s Core from Experimentally-Based Conductive Heat Flow Estimates

2022· article· en· W4310679616 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueCrystals · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicHigh-pressure geophysics and materials
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectrical resistivity and conductivityThermal conductivityHeat fluxMaterials scienceConvectionThermalCore (optical fiber)Flux (metallurgy)Heat flowElectrical conductorAdiabatic processAnalytical Chemistry (journal)ThermodynamicsCondensed matter physicsHeat transferComposite materialMetallurgyChemistryPhysics

Abstract

fetched live from OpenAlex

Electrical resistivity measurements of Fe-5 wt% Ni were made in situ under pressures of 2–5 GPa and temperatures up to 2000 K in a cubic-anvil press. The thermal conductivity was calculated from the measured electrical resistivity data using the Wiedemann–Franz law. Comparison of these data with previous studies on pure Fe and Fe-10 wt% Ni shows that a change in the Ni content within the range 0–10 wt% Ni has no significant effect on electrical resistivity of Fe alloys. Comparing the estimated adiabatic core heat flux of ~331 MW at the top of Vesta’s core to the range of estimated heat flux through the CMB of 1.5–78 GW, we infer that the mechanism stirring Vesta’s liquid outer core to generate its surface magnetic field tens of millions of years ago in its early history was thermal convection.

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.433
Threshold uncertainty score0.999

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)0.0140.000

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 head0.022
GPT teacher head0.231
Teacher spread0.208 · 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