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Record W3166377847

Geochemical Advances in Mercury Science Facilitated by a Landed Mission

2020· article· en· W3166377847 on OpenAlexaff
K. E. Vander Kaaden, C. M. Ernst, N. L. Chabot, R. L. Klima, P. N. Peplowski, E. B. Rampe, S. Besse, D. T. Blewett, P. K. Byrne, B. W. Denevi, Sander Goossens, S. A. Hauck, N. R. Izenberg, C. L. Johnson, L. M. Jozwiak, H. Korth, R. L. McNutt, S. L. Murchie, J. M. Raines, M. S. Thompson, Ronald J. Vervack

Bibliographic record

VenueLunar and Planetary Science Conference · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMercury (programming language)AstrobiologyOrbiterPlanetTerrestrial planetGeologyEnvironmental scienceEarth scienceAstronomyPhysicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

The data from the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft have revealed several surprising characteristics about the surface of Mercury, leading to its classification as a geochemical endmember among the terrestrial planets. Some of these features include elevated abundances of up to 3 wt% S, C enrichment as high as 4 wt% over the local mean in low reflectance materials (LRM), Na up to 5 wt% at high northern latitudes, and Fe abundances typically lower than 2 wt% [e.g., 1–4]. The S and Fe concentrations have been used to infer that Mercury’s igneous history evolved under highly reduced oxygen fugacity conditions between 2.6 and 7.3 log10 units below the iron-wustite buffer [e.g., 5], which is more reducing than any other terrestrial planet in the solar system [e.g., 6]. This highly reduced nature has important consequences for the differentiation and thermal/magmatic evolution of Mercury. While the immense amount of data collected by MESSENGER revealed Mercury as a geochemical endmember, this new knowledge gained raised additional questions that necessitate continued exploration of the planet. Fortunately, BepiColombo launched in October of 2018, and this joint ESA/JAXA dual-orbiter spacecraft is the most ambitious effort yet attempted to explore Mercury [e.g., 7]. Looking beyond BepiColombo, there are major aspects of Mercury’s geochemical character and evolution for which significant knowledge gaps can be dramatically improved with data acquired from the planet’s surface via in situ landed science.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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