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Record W1537080486 · doi:10.1002/2015gl064988

Imprints of impulse‐excited hydromagnetic waves on electrons in the Van Allen radiation belts

2015· article· en· W1537080486 on OpenAlexaff
Xu‐Zhi Zhou, Zihan Wang, Qiugang Zong, S. G. Claudepierre, I. R. Mann, M. G. Kivelson, V. Angelopoulos, Yixin Hao, Yong‐Fu Wang, Z. Y. Pu

Bibliographic record

VenueGeophysical Research Letters · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersNational Natural Science Foundation of China
KeywordsPhysicsMagnetosphereVan Allen radiation beltVan Allen ProbesElectronImpulse (physics)Electromagnetic radiationExcited stateComputational physicsAtomic physicsEnergy fluxResonance (particle physics)RadiationGeophysicsQuantum electrodynamicsPlasmaClassical mechanicsOpticsAstronomyNuclear physics

Abstract

fetched live from OpenAlex

Abstract Ultralow frequency electromagnetic oscillations, interpreted as standing hydromagnetic waves in the magnetosphere, are a major energy source that accelerates electrons to relativistic energies in the Van Allen radiation belt. Electrons can rapidly gain energy from the waves when they resonate via a process called drift resonance, which is observationally characterized by energy‐dependent phase differences between electron flux and electromagnetic oscillations. Such dependence has been recently observed and interpreted as spacecraft identifications of drift resonance electron acceleration. Here we show that in the initial wave cycles, the observed phase relationship differs from that characteristic of well‐developed drift resonance. We further examine the differences and find that they are imprints of impulse‐excited, coupled fast‐Alfvén waves before they transform into more typical standing waves. Our identification of such imprints provides a new understanding of how energy couples in the inner magnetosphere, and a new diagnostic for the generation and growth of magnetospheric hydromagnetic pulsations.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.561
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.021
GPT teacher head0.300
Teacher spread0.279 · 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

Citations48
Published2015
Admission routes1
Has abstractyes

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