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Record W2139559534 · doi:10.5194/angeo-32-1477-2014

On the origin of falling-tone chorus elements in Earth's inner magnetosphere

2014· article· en· W2139559534 on OpenAlexaff
H. Breuillard, O. V. Agapitov, Anton Artemyev, V. Krasnoselskikh, O. Le Contel, C. M. Cully, V. Angelopoulos, Yu. Zaliznyak, G. Rolland

Bibliographic record

VenueAnnales Geophysicae · 2014
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsChorusMagnetospherePhysicsGeophysicsVan Allen radiation beltAmplitudeEquatorMagnetic fieldLatitudeAstronomyOptics

Abstract

fetched live from OpenAlex

Abstract. Generation of extremely/very low frequency (ELF/VLF) chorus waves in Earth's inner magnetosphere has received increased attention recently because of their significance for radiation belt dynamics. Though past theoretical and numerical models have demonstrated how rising-tone chorus elements are produced, falling-tone chorus element generation has yet to be explained. Our new model proposes that weak-amplitude falling-tone chorus elements can be generated by magnetospheric reflection of rising-tone elements. Using ray tracing in a realistic plasma model of the inner magnetosphere, we demonstrate that rising-tone elements originating at the magnetic equator propagate to higher latitudes. Upon reflection there, they propagate to lower L-shells and turn into oblique falling tones of reduced power, frequency, and bandwidth relative to their progenitor rising tones. Our results are in good agreement with comprehensive statistical studies of such waves, notably using magnetic field measurements from THEMIS (Time History of Events and Macroscale Interactions during Substorms) spacecraft. Thus, we conclude that the proposed mechanism can be responsible for the generation of weak-amplitude falling-tone chorus emissions.

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 categoriesInsufficient payload (model declined to judge)
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 score0.357
Threshold uncertainty score1.000

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 integrity0.0000.000
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 head0.008
GPT teacher head0.236
Teacher spread0.228 · 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.

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

Citations10
Published2014
Admission routes1
Has abstractyes

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