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Record W2902276125 · doi:10.1029/2018gl080635

Nonlinear Coupling Between Whistler‐Mode Chorus and Electron Cyclotron Harmonic Waves in the Magnetosphere

2018· article· en· W2902276125 on OpenAlexaff
Zhonglei Gao, Zhenpeng Su, Fuliang Xiao, Danny Summers, Nigang Liu, Huinan Zheng, Yuming Wang, Fengsi Wei, Shui Wang

Bibliographic record

VenueGeophysical Research Letters · 2018
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPhysicsMagnetosphereChorusElectronWhistlerComputational physicsDispersion relationHarmonicVan Allen radiation beltElectron precipitationParticle accelerationElectromagnetic radiationCyclotronQuantum electrodynamicsAtomic physicsPlasmaOpticsAcousticsQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract Electromagnetic whistler‐mode chorus and electrostatic electron cyclotron harmonic (ECH) waves can contribute significantly to auroral electron precipitation and radiation belt electron acceleration. In the past, linear and nonlinear wave‐particle interactions have been proposed to explain the occurrences of these magnetospheric waves. By analyzing Van Allen Probes data, we present here the first evidence for nonlinear coupling between chorus and ECH waves. The sum‐frequency and difference‐frequency interactions produced the ECH sidebands with discrete frequency sweeping structures exactly corresponding to the chorus rising tones. The newly generated weak sidebands did not satisfy the original electrostatic wave dispersion relation. After the generation of chorus and normal ECH waves by hot electron instabilities, the nonlinear wave‐wave interactions could additionally redistribute energy among the resonant waves, potentially affecting to some extent the magnetospheric electron dynamics.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 head0.019
GPT teacher head0.313
Teacher spread0.294 · 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 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

Citations19
Published2018
Admission routes1
Has abstractyes

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