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Record W4282003379 · doi:10.1051/swsc/2022023

Observations and modeling of scintillation in the vicinity of a polar cap patch

2022· article· en· W4282003379 on OpenAlexfundno aff
Leslie Lamarche, K. Deshpande, M. D. Zettergren

Bibliographic record

VenueJournal of Space Weather and Space Climate · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersEmbry-Riddle Aeronautical UniversityUniversity of CalgaryNational Science Foundation
KeywordsScintillationIonosphereInterplanetary scintillationPhysicsSatelliteRemote sensingSIGNAL (programming language)Scale (ratio)PolarGeophysicsPlasmaGeologyEnvironmental scienceAstronomyOpticsComputer scienceSolar windNuclear physicsDetector

Abstract

fetched live from OpenAlex

Small-scale ionospheric plasma structures can cause scintillation in radio signals passing through the ionosphere. The relationship between the scintillated signal and how plasma structuring develops is complex. We model the development of small-scale plasma structuring in and around an idealized polar cap patch observed by the Resolute Bay Incoherent Scatter Radars (RISR) with the Geospace Environment Model for Ion-Neutral Interactions (GEMINI). Then, we simulate a signal passing through the resulting small-scale structuring with the Satellite-beacon Ionospheric-scintillation Global Model of the upper Atmosphere (SIGMA) to predict the scintillation characteristics that will be observed by a ground receiver at different stages of instability development. Finally, we compare the predicted signal characteristics with actual observations of scintillation from ground receivers in the vicinity of Resolute Bay. We interpret the results in terms of the nature of the small-scale plasma structuring in the ionosphere and how it impacts signals of different frequencies and attempt to infer information about the ionospheric plasma irregularity spectrum.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.645
Threshold uncertainty score0.218

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 studies0.0000.000
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 head0.016
GPT teacher head0.240
Teacher spread0.224 · 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

Citations15
Published2022
Admission routes1
Has abstractyes

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