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Record W4292074780 · doi:10.1029/2022gl099655

Quantifying the Size and Duration of a Microburst‐Producing Chorus Region on 5 December 2017

2022· article· en· W4292074780 on OpenAlexaff
S. S. Elliott, A. W. Breneman, C. A. Colpitts, Joshua Pettit, C. A. Cattell, Alexa Halford, Mykhaylo Shumko, J. G. Sample, A. Johnson, Yoshizumi Miyoshi, Yoshiya Kasahara, C. M. Cully, Satoko Nakamura, Takefumi Mitani, Tomoaki Hori, Iku Shinohara, K. Shiokawa, Shoya Matsuda, Martin Connors, Mitsunori Ozaki, J. Manninen

Bibliographic record

VenueGeophysical Research Letters · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsAthabasca UniversityUniversity of Calgary
FundersNational Aeronautics and Space Administration
KeywordsChorusMicroburstDuration (music)Environmental scienceMeteorologyAtmospheric sciencesGeologyClimatologyGeographyPhysicsAcousticsWind shearWind speed

Abstract

fetched live from OpenAlex

Abstract Microbursts are impulsive (<1 s) injections of electrons into the atmosphere, thought to be caused by nonlinear scattering by chorus waves. Although attempts have been made to quantify their contribution to outer belt electron loss, the uncertainty in the overall size and duration of the microburst region is typically large, so that their contribution to outer belt loss is uncertain. We combine datasets that measure chorus waves (Van Allen Probes [RBSP], Arase, ground‐based VLF stations) and microburst (>30 keV) precipitation (FIREBIRD II and AC6 CubeSats, POES) to determine the size of the microburst‐producing chorus source region beginning on 5 December 2017. We estimate that the long‐lasting (∼30 hr) microburst‐producing chorus region extends from 4 to 8 MLT and 2–5 L. We conclude that microbursts likely represent a major loss source of outer radiation belt electrons for this event.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.039
GPT teacher head0.307
Teacher spread0.268 · 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

Citations8
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueGeophysical Research Letters→Same topicIonosphere and magnetosphere dynamics→French-language works237,207→