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Record W3211936555 · doi:10.1002/essoar.10503286.1

A first comparison between ionospheric and surface level magnetic fields at Mars

2020· article· en· W3211936555 on OpenAlexaff
Matthew Fillingim, C. L. Johnson, Anna Mittelholz, B. Langlais, C. T. Russell, S. P. Joy, Peter Chi, R. J. Lillis, J. R. Espley, S. E. Smrekar, W. B. Banerdt, B. M. Jakosky

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of British Columbia
FundersNational Aeronautics and Space Administration
KeywordsIonosphereMars Exploration ProgramGeophysicsMagnetic fieldEarth's magnetic fieldCurrent (fluid)GeologyPhysicsGeodesyAtmospheric sciencesAstrobiology

Abstract

fetched live from OpenAlex

With both the Mars Atmosphere and Volatile Evolution (MAVEN) mission and the Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) mission concurrently operating at Mars, we are able to make two point comparisons of the vector magnetic field at Mars for the first time. During MAVEN overflights of the InSight landing site, we compared deviations in the ionospheric magnetic field to variations in the surface level magnetic field. We find significant orbit to orbit variability in the magnitude and direction of the ionospheric magnetic field as well as significant day to day variability of the surface level magnetic field. We attribute this variability to time varying ionospheric currents. However, when analyzing the ensemble of 16 individual MAVEN overflights of the InSight landing location, we see no clear correlation between the magnitudes or directions of the ionospheric magnetic field and the surface magnetic field as might be expected. If the presumed ionospheric currents have a small scale size, then the ionospheric magnetic field will display increased variability as MAVEN flies through the current structure. Whereas the present analysis is restricted to mostly nightside MAVEN overflights where current are expected to be weak, future analyses should incorporate dayside overflights where current are expected to be stronger and current signatures more clear.

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)0.001
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.050
GPT teacher head0.233
Teacher spread0.183 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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