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Record W2790305234 · doi:10.1002/2018gl077298

Evidence for Neutrals‐Foreshock Electrons Impact at Mars

2018· article· en· W2790305234 on OpenAlexaff
C. Mazelle, K. Meziane, D. L. Mitchell, Philippe Garnier, J. R. Espley, A. M. Hamza, J. S. Halekas, B. M. Jakosky

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of New Brunswick
FundersCentre National d’Etudes Spatiales
KeywordsPhysicsExosphereSolar windForeshockMars Exploration ProgramBow shock (aerodynamics)ElectronFlux (metallurgy)Interplanetary spaceflightGeophysicsComputational physicsAtomic physicsPlasmaAstrobiologyShock waveIonGeologyMechanicsNuclear physicsMaterials science

Abstract

fetched live from OpenAlex

Abstract Backstreaming electrons emanating from the bow shock of Mars reported from the Mars Atmosphere and Volatile EvolutioN/Solar Wind Electron Analyzer observations show a flux fall off with the distance from the shock. This feature is not observed at the terrestrial foreshock. The flux decay is observed only for electron energy E ≥ 29 eV. A reported recent study indicates that Mars foreshock electrons are produced at the shock in a mirror reflection of a portion of the solar wind electrons. In this context, and given that the electrons are sufficiently energetic to not be affected by the interplanetary magnetic field fluctuations, the observed flux decrease appears problematic. We investigate the possibility that the flux fall off with distance results from the impact of backstreaming electrons with Mars exospheric neutral hydrogen. We demonstrate that the flux fall off is consistent with the electron‐atomic hydrogen impact cross section for a large range of energy. A better agreement is obtained for energy where the impact cross section is the highest. One important consequence is that foreshock electrons can play an important role in the production of pickup ions at Mars far exosphere.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.114
GPT teacher head0.396
Teacher spread0.282 · 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.

Study designBench or experimental
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

Citations14
Published2018
Admission routes1
Has abstractyes

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