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Record W2982554803 · doi:10.1029/2019gl085037

Collisionless Electron Dynamics in the Magnetosheath of Mars

2019· article· en· W2982554803 on OpenAlexaff
S. J. Schwartz, L. Andersson, Shaosui Xu, D. L. Mitchell, Hassanali Akbari, R. E. Ergun, C. Mazelle, S. A. Thaller, A. R. N. Sales, Konstantinos Horaites, G. A. DiBraccio, K. Meziane

Bibliographic record

VenueGeophysical Research Letters · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsUniversity of New Brunswick
FundersCentre National d’Etudes SpatialesNational Aeronautics and Space Administration
KeywordsMagnetosheathBow shock (aerodynamics)PhysicsElectronMars Exploration ProgramSolar windPopulationComputational physicsIonizationExosphereKinetic energyShock (circulatory)Shock waveAtomic physicsMagnetopausePlasmaMechanicsAstronomyClassical mechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract Electron velocity distributions in Mars's magnetosheath show a systematic erosion of the energy spectrum with distance downstream from the bow shock. Previous attempts to model this erosion invoked assumptions to promote electron ionization impact collisions with Mars's neutral hydrogen exosphere. We show that the near collision‐free magnetosheath requires a kinetic description; the population of electrons at any location is a convolution of electrons arriving from more distant regions that ultimately map directly to the solar wind. We construct a simple model that captures all the essential physics. The model demonstrates how the erosion of the electron distributions is the result of the trapping, escape, and replacement of electrons that traverse the global bow shock; some are temporarily confined to the expanding cavity formed by the cross‐shock electrostatic potential. The model also has implications for the ability of solar wind electrons to reach altitudes below the pileup boundary.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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 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

Citations13
Published2019
Admission routes1
Has abstractyes

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