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Record W2002219117 · doi:10.1029/2004ja010437

Competition between acceleration and loss mechanisms of relativistic electrons during geomagnetic storms

2004· article· en· W2002219117 on OpenAlexaff
Danny Summers, Chunyu Ma, T. Mukai

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPhysicsVan Allen radiation beltElectronHissComputational physicsGeomagnetic stormPitch angleWhistlerElectron precipitationAmplitudeDiffusionMagnetosphereAtomic physicsCyclotronEarth's magnetic fieldGeophysicsPlasmaMagnetic fieldNuclear physicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

We demonstrate quantitatively that whether a geomagnetic storm results in an increase or decrease of relativistic electrons in the outer zone depends on the competition between the physical processes producing the energization and loss of electrons. We construct a simplified one‐dimensional model for the electron energy distribution incorporating electron energization by cyclotron resonant interaction with whistler‐mode chorus, and electron losses due to pitch angle scattering into the loss cone by combined plasma waves (in particular, electromagnetic ion cyclotron waves and plasmaspheric hiss). We do not include radial diffusion explicitly since the model applies to the region 3 < L < 5 where radial diffusion is expected to be weak. We treat the chorus wave amplitude and electron loss rate as model input variables and compute the solution for the electron energy distribution as the model output. The extent of the electron flux increase or decrease during the event is found to be sensitively controlled by the magnitudes of the wave amplitude and electron loss rate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.547

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 studies0.0000.000
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 head0.015
GPT teacher head0.283
Teacher spread0.268 · 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 designTheoretical or conceptual
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

Citations76
Published2004
Admission routes1
Has abstractyes

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