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Record W2022717084 · doi:10.1002/2013ja019223

The quasi‐electrostatic mode of chorus waves and electron nonlinear acceleration

2014· article· en· W2022717084 on OpenAlexaff
O. V. Agapitov, Anton Artemyev, D. Mourenas, V. Krasnoselskikh, J. W. Bonnell, O. Le Contel, C. M. Cully, V. Angelopoulos

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
FundersCentre National d’Etudes Spatiales
KeywordsPhysicsMagnetosphereElectronParticle accelerationComputational physicsAccelerationAmplitudeResonance (particle physics)ChorusQuantum electrodynamicsAtomic physicsClassical mechanicsPlasmaOpticsNuclear physics

Abstract

fetched live from OpenAlex

Selected Time History of Events and Macroscale Interactions During Substorms observations at medium latitudes of highly oblique and high‐amplitude chorus waves are presented and analyzed. The presence of such very intense waves is expected to have important consequences on electron energization in the magnetosphere. An analytical model is therefore developed to evaluate the efficiency of the trapping and acceleration of energetic electrons via Landau resonance with such nearly electrostatic chorus waves. Test‐particle simulations are then performed to illustrate the conclusions derived from the analytical model, using parameter values consistent with observations. It is shown that the energy gain can be much larger than the initial particle energy for 10 keV electrons, and it is further demonstrated that this energy gain is weakly dependent on the density variation along field lines.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 integrity0.0000.000
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 head0.013
GPT teacher head0.326
Teacher spread0.312 · 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 designSimulation or modeling
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

Citations88
Published2014
Admission routes1
Has abstractyes

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