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Record W2568266067 · doi:10.1002/2016ja022812

Investigating energetic electron precipitation through combining ground‐based and balloon observations

2017· article· en· W2568266067 on OpenAlexaff
Mark A. Clilverd, Craig J. Rodger, M. McCarthy, R. M. Millan, Lauren Blum, Neil Cobbett, J. B. Brundell, D. W. Danskin, Alexa Halford

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsNatural Resources Canada
FundersBritish Antarctic SurveyMarsden FundNatural Environment Research CouncilSight Research UKDartmouth CollegeNational Aeronautics and Space AdministrationNational Science Foundation
KeywordsRiometerElectron precipitationPhysicsVan Allen radiation beltPrecipitationElectronCyclotronComputational physicsMagnetosphereSpectral lineAstrophysicsGeophysicsAtmospheric sciencesIonosphereMagnetic fieldAstronomyMeteorologyNuclear physics

Abstract

fetched live from OpenAlex

Abstract A detailed comparison is undertaken of the energetic electron spectra and fluxes of two precipitation events that were observed in 18/19 January 2013. A novel but powerful technique of combining simultaneous ground‐based subionospheric radio wave data and riometer absorption measurements with X‐ray fluxes from a Balloon Array for Relativistic Radiation‐belt Electron Losses (BARREL) balloon is used for the first time as an example of the analysis procedure. The two precipitation events are observed by all three instruments, and the relative timing is used to provide information/insight into the spatial extent and evolution of the precipitation regions. The two regions were found to be moving westward with drift periods of 5–11 h and with longitudinal dimensions of ~20° and ~70° (1.5–3.5 h of magnetic local time). The electron precipitation spectra during the events can be best represented by a peaked energy spectrum, with the peak in flux occurring at ~1–1.2 MeV. This suggests that the radiation belt loss mechanism occurring is an energy‐selective process, rather than one that precipitates the ambient trapped population. The motion, size, and energy spectra of the patches are consistent with electromagnetic ion cyclotron‐induced electron precipitation driven by injected 10–100 keV protons. Radio wave modeling calculations applying the balloon‐based fluxes were used for the first time and successfully reproduced the ground‐based subionospheric radio wave and riometer observations, thus finding strong agreement between the observations and the BARREL measurements.

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 score0.086
Threshold uncertainty score0.735

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.059
GPT teacher head0.346
Teacher spread0.287 · 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

Citations35
Published2017
Admission routes1
Has abstractyes

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