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Record W2086771584 · doi:10.1029/2003je002158

Comparisons of electron fluxes measured in the crustal fields at Mars by the MGS magnetometer/electron reflectometer instrument with a <i>B</i> field–dependent transport code

2003· article· en· W2086771584 on OpenAlexfundno aff
M. W. Liemohn, D. L. Mitchell, A. F. Nagy, Jane L. Fox, Tamara W. Reimer, Yingjuan Ma

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
FundersAssociation of Canadian Universities for Northern StudiesUniversity of MichiganNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsPhysicsMars Exploration ProgramGeophysicsMagnetometerComputational physicsElectronMagnetic fieldSolar windScatteringGeologyOpticsAstronomyNuclear physics

Abstract

fetched live from OpenAlex

We compare Mars Global Surveyor (MGS) magnetometer/electron reflectometer data with results from a B field–dependent kinetic transport code for “superthermal” electrons. The photoelectrons created on crustal field loops, when they are on the dayside, allow for the exploration of the magnetic topology and the upper atmospheric density structure. A case study of a typical orbit of the MGS satellite through the strong crustal field region in the southern hemisphere of Mars is examined. The results indicate that the low solar wind dynamic pressure during the selected orbit allowed for the expansion of the crustal field line to relatively high altitudes. Another feature of the photoelectrons in the crustal field region is that the distribution at high energies ( E &gt; 100 eV) is far more isotropic than what is expected from collisional scattering processes alone. Several candidate processes are discussed that might be preferentially scattering high‐energy electrons. A final conclusion is that a two‐stream model is inadequate for effectively examining photoelectron pitch angle distributions at Mars in the presence of the crustal fields.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.350

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 integrity0.0000.001
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 head0.033
GPT teacher head0.304
Teacher spread0.271 · 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 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

Citations43
Published2003
Admission routes1
Has abstractyes

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