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Record W4313812604 · doi:10.1029/2022je007616

Mars' External Magnetic Field as Seen From the Surface With InSight

2023· article· en· W4313812604 on OpenAlexafffund
Anna Mittelholz, C. L. Johnson, Matthew Fillingim, R. E. Grimm, S. P. Joy, Shea N. Thorne, W. B. Banerdt

Bibliographic record

VenueJournal of Geophysical Research Planets · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaJet Propulsion Laboratory
KeywordsMartianMagnetometerMars Exploration ProgramInterplanetary magnetic fieldMagnetic fieldGeophysicsPhysicsAstrobiologyMercury's magnetic fieldMartian surfaceInterplanetary spaceflightField (mathematics)GeologySolar wind

Abstract

fetched live from OpenAlex

Abstract The magnetometer of the InSight mission operated on the Martian surface from November 2018 until May 2022. Previously, satellites have provided information on the Martian magnetic field environment from orbit; however, the degree to which external fields penetrate to and interact with the surface could not be studied prior to the InSight landing. Here, we present an overview of the complete surface magnetic field data from InSight sols 14 to 1241 that display different external magnetic field phenomena, transient and periodic. Periodic observations range from short period waves (100–1000s of seconds), diurnal variations, ∼26 sol Carrington rotations, to seasonal fluctuations. Transient events are observed in response to space weather and dust movement. We find that ionospheric variations are the dominant contribution as seen from the surface, while contributions from the undisturbed interplanetary magnetic field are more subtle. We discuss limitations associated with a single point measurement and opportunities that future missions could enable. Including magnetometers on future missions at a variety of locations for long‐duration continuous observations will be of great value in understanding a range of external field phenomena and will enable further investigations in different crustal magnetic field settings.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.036
GPT teacher head0.309
Teacher spread0.273 · 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

Citations19
Published2023
Admission routes2
Has abstractyes

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