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Record W4406578827 · doi:10.1029/2023je008111

Aqueous Alteration as an Origin of Martian Magnetization

2025· article· en· W4406578827 on OpenAlexaff
B. Bultel, M. A. Wieczorek, Anna Mittelholz, C. L. Johnson, J. Gattacceca, Valentin Fortier, B. Langlais

Bibliographic record

VenueJournal of Geophysical Research Planets · 2025
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of British Columbia
FundersAgence Nationale de la Recherche
KeywordsMagnetiteGeologyMartianMagnetizationMars Exploration ProgramCrustBasaltGeophysicsMagnetic anomalyMagnetic fieldMartian surfaceRock magnetismGeochemistryMineralogyRemanenceAstrobiologyPaleontologyPhysics

Abstract

fetched live from OpenAlex

Abstract Strong magnetic fields have been measured from orbit around Mars over parts of the ancient southern highlands crust and on the surface at the InSight landing site. The geological processes that are responsible for generating strong magnetization within the crust remain poorly understood. One possibility is that intense aqueous alteration of crustal materials, through the process of serpentinization, could have produced magnetite that was magnetized in the presence of a global core‐generated magnetic field. Here, we test this idea with geophysical and geochemical models. We first determine the magnetizations required to account for the observed magnetic field strengths and then estimate the amount of magnetite necessary to account for these magnetizations. For the strongest orbital magnetic field strengths, about 7 wt% magnetite is required if the magnetic layer is 10 km thick. For the surface field strength observed at the InSight landing site, 0.4–1.1 wt% magnetite is required if the magnetic layer corresponds to one or more of the three crustal layers observed in the InSight seismic data (with thicknesses from 8 to 39 km). We then investigate the minerals that are produced by aqueous alteration for various possible crustal compositions and water‐to‐rock ratios using a thermodynamic model. Magnetite abundances up to 6 wt% can be generated for dunitic compositions that could account for the strongest magnetic anomalies. For more representative basaltic starting compositions, however, more than 0.4 wt% can only be generated when using high water‐to‐rock ratios, which could account for the weaker magnetizations beneath the InSight landing site.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.397
Threshold uncertainty score0.223

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.359
Teacher spread0.325 · 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 designTheoretical or conceptual
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

Citations6
Published2025
Admission routes1
Has abstractyes

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