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Record W1557546047 · doi:10.1126/science.aaa8720

Low-altitude magnetic field measurements by MESSENGER reveal Mercury’s ancient crustal field

2015· article· en· W1557546047 on OpenAlexaff
C. L. Johnson, R. J. Phillips, Michael E. Purucker, B. J. Anderson, P. K. Byrne, B. W. Denevi, Joshua M. Feinberg, S. A. Hauck, J. W. Head, H. Korth, P. B. James, E. Mazarico, G. A. Neumann, L. Philpott, M.A. Siegler, N. A. Tsyganenko, Sean C. Solomon

Bibliographic record

VenueScience · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMercury (programming language)PlanetAstrobiologyGeologyGeophysicsMagnetic fieldPaleomagnetismAstrophysicsPhysics

Abstract

fetched live from OpenAlex

Magnetized rocks can record the history of the magnetic field of a planet, a key constraint for understanding its evolution. From orbital vector magnetic field measurements of Mercury taken by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft at altitudes below 150 kilometers, we have detected remanent magnetization in Mercury's crust. We infer a lower bound on the average age of magnetization of 3.7 to 3.9 billion years. Our findings indicate that a global magnetic field driven by dynamo processes in the fluid outer core operated early in Mercury's history. Ancient field strengths that range from those similar to Mercury's present dipole field to Earth-like values are consistent with the magnetic field observations and with the low iron content of Mercury's crust inferred from MESSENGER elemental composition data.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.260
Teacher spread0.228 · 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 designObservational
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

Citations102
Published2015
Admission routes1
Has abstractyes

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