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Record W3065208261 · doi:10.1029/2020gl089138

Potential Evidence of Low‐Energy Electron Scattering and Ionospheric Precipitation by Time Domain Structures

2020· article· en· W3065208261 on OpenAlexaff
Yangyang Shen, Anton Artemyev, Xiao‐Jia Zhang, I. Y. Vasko, A. Runov, V. Angelopoulos, D. J. Knudsen

Bibliographic record

VenueGeophysical Research Letters · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Calgary
FundersNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsElectron precipitationElectronPhysicsPlasma sheetIonosphereScatteringWhistlerAtomic physicsMagnetospherePlasmaComputational physicsGeophysicsNuclear physicsOptics

Abstract

fetched live from OpenAlex

Abstract Plasma sheet electron precipitation is critical in magnetosphere‐ionosphere coupling and has long been attributed to electron scattering by whistler‐mode and electron cyclotron harmonic waves. Recent observations have revealed that time domain structures (TDSs) that appear as broadband electrostatic fluctuations may also scatter plasma sheet electrons. However, there has been no observational evidence of TDS scattering electrons into the ionosphere. This study presents potential evidence from conjugate observations between the Time History of Events and Macroscale Interactions during Substorms (THEMIS) mission and the low‐altitude Enhanced Polar Outflow Probe (e‐POP) spacecraft. During the five events presented, THEMIS observed intense electron injections accompanied by TDSs, while e‐POP captured precipitation of plasma sheet electrons with energies ∼ 100–325 eV over a broad pitch angle range. The observed TDSs can efficiently scatter these electrons exceeding the strong diffusion limit. Our results suggest that TDSs may contribute to plasma sheet electron scattering around times of injections.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.334
Threshold uncertainty score0.590

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)0.0000.000

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 head0.009
GPT teacher head0.259
Teacher spread0.251 · 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 designBench or experimental
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

Citations30
Published2020
Admission routes1
Has abstractyes

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