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Record W3129565381 · doi:10.1029/2020ja028968

GPS Scintillations and TEC Variations in Association With a Polar Cap Arc

2021· article· en· W3129565381 on OpenAlexaff
Yong Wang, Zheng Cao, Zan‐Yang Xing, Qinghe Zhang, P. T. Jayachandran, Kjellmar Oksavik, N. Balan, K. Shiokawa

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2021
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of New Brunswick
FundersJapan Society for the Promotion of ScienceNorges ForskningsrådChina Postdoctoral Science FoundationNational Natural Science Foundation of China
KeywordsTECGeologyIonosondeGeodesyGlobal Positioning SystemIonospherePolarGeophysicsTotal electron contentInterplanetary magnetic fieldAmplitudePhysicsSolar windOpticsElectron densityAstronomyPlasmaTelecommunicationsComputer science

Abstract

fetched live from OpenAlex

Abstract A unique example of a polar cap arc producing clear amplitude and phase scintillations in GPS L‐band signals is presented using observations from an all‐sky imager and a GPS receiver and a digital ionosonde at Resolute Bay and the SuperDARN Inuvik radar. During the southward interplanetary magnetic field (IMF) condition, the polar cap arc moved quickly from the dusk‐side to the midnight auroral oval at a speed of ∼700 m/s, as revealed by all‐sky 557.7 and 630.0 nm images. When it intersected the raypath of GPS signals, both amplitude and phase scintillations appeared, which is very different from previous results. Moreover, the scintillations were precisely determined through power spectral analysis. We propose that the strong total electron content (TEC) enhancement (∼6 TECU) and flow shears in association with the polar cap arc under the southward IMF condition were creating the scintillations. It provides evidence for the existence of polar cap arc scintillations that may be harmful for satellite applications even through L‐band signals.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.027
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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