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Record W6917698520 · doi:10.57757/iugg23-0951

Using multipoint observations to quantify microburst precipitation caused by whistler mode chorus waves

2023· article· en· W6917698520 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePublication Database GFZ (GFZ German Research Centre for Geosciences) · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsAthabasca UniversityUniversity of Calgary
Fundersnot available
KeywordsMicroburstChorusFlux (metallurgy)Electron precipitationPrecipitationVan Allen radiation beltConjunction (astronomy)Scattering

Abstract

fetched live from OpenAlex

<!--!introduction!--><b></b> Microbursts are impulsive injections of energetic (few keV to MeV) electrons into the atmosphere, primarily caused by nonlinear scattering by whistler mode chorus waves. While the relative importance of microburst precipitation as a loss process has not been fully quantified, many studies have shown microbursts may be a major loss source for outer radiation belt electrons. Conjunction observations between the FIREBIRD II CubeSats and Van Allen Probes (RBSP) from 2015 – 2019 have presented the opportunity to quantify the importance of microburst precipitation. We utilize this conjunction dataset, along with additional observations of chorus and microburst precipitation, when available, to constrain the size of the microburst-producing chorus region. We will present statistical results for the upper and lower bounds on the size of the region. Additionally, we will discuss wave properties, including amplitude, wave normal angle, duration, and microburst properties including flux and duration to further understand the observable dependence.&nbsp;

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.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
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 head0.091
GPT teacher head0.376
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