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Record W3018000489 · doi:10.5194/angeo-38-575-2020

Plasma density gradients at the edge of polar ionospheric holes: the absence of phase scintillation

2020· article· en· W3018000489 on OpenAlexfundno aff
Luke Jenner, Alan Wood, Gareth Dorrian, Kjellmar Oksavik, T. K. Yeoman, A. R. Fogg, A. J. Coster

Bibliographic record

VenueAnnales Geophysicae · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersScience and Technology Facilities CouncilNorges ForskningsrådNottingham Trent UniversityMassachusetts Institute of TechnologyUniversitetet i BergenTrent UniversityNational Science Foundation
KeywordsScintillationIonosphereInterplanetary scintillationSolsticeAtmospheric sciencesElectron densityIncoherent scatterPolarNorthern HemispherePhysicsElectron precipitationGeophysicsPlasmaGeologyLatitudeOpticsSolar windAstronomyCoronal mass ejectionMagnetosphere

Abstract

fetched live from OpenAlex

Abstract. Polar holes were observed in the high-latitude ionosphere during a series of multi-instrument case studies close to the Northern Hemisphere winter solstice in 2014 and 2015. These holes were observed during geomagnetically quiet conditions and under a range of solar activities using the European Incoherent Scatter (EISCAT) Svalbard Radar (ESR) and measurements from Global Navigation Satellite System (GNSS) receivers. Steep electron density gradients have been associated with phase scintillation in previous studies; however, no enhanced scintillation was detected within the electron density gradients at these boundaries. It is suggested that the lack of phase scintillation may be due to low plasma density levels and a lack of intense particle precipitation. It is concluded that both significant electron density gradients and plasma density levels above a certain threshold are required for scintillation to occur.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.393

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 head0.011
GPT teacher head0.231
Teacher spread0.220 · 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 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

Citations6
Published2020
Admission routes1
Has abstractyes

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