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Record W4293367095 · doi:10.1029/2022ja030698

Analysis of Radiation Belt “Killer” Electron Energy Spectra

2022· article· en· W4293367095 on OpenAlexaff
Danny Summers, Sarah Stone

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsVan Allen radiation beltPhysicsElectronAtomic physicsSpectral lineKinetic energyPower lawElectromagnetic radiationComputational physicsMagnetic fieldQuantum mechanicsMagnetosphere

Abstract

fetched live from OpenAlex

Abstract Highly energetic (>1 MeV) electrons are typically generated in the Earth's outer radiation belt during geomagnetically disturbed times. Such “killer” electrons can be produced by electron cyclotron resonance with whistler‐mode waves. We model this process by a relativistic Fokker‐Planck diffusion equation for the electron distribution function f ( E ), where E is the normalized electron kinetic energy. The equation involves an energy diffusion coefficient D ( E ) and an advection coefficient A ( E ), which depend on the wave spectral energy density. For two types of wave energy spectrum, a Gaussian and a power law with spectral index q , we seek large‐ E steady‐state solutions for f ( E ). For lower‐band chorus, for both Gaussian and power law spectra, we find that with k = D 0 T 0 , where D 0 is a diffusion parameter and T 0 is the e‐folding timescale for electron loss. For a full‐band whistler spectrum, we find that if 2 < q < 4 then ; in the special case q = 4, we obtain the power law solution f ∼ E − δ , where . We compare the analytical electron spectra obtained with the phase‐space density profiles observed by the Van Allen Probes.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.685

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.297
Teacher spread0.285 · 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

Citations17
Published2022
Admission routes1
Has abstractyes

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