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Record W2775328033 · doi:10.1134/s0010952517060077

Large-scale irregularities of the winter polar topside ionosphere according to data from Swarm satellites

2017· article· en· W2775328033 on OpenAlexfundno aff
Renata Lukianova, Ш. Р. Богоутдинов

Bibliographic record

VenueCosmic Research · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsIonospherePhysicsPolarConvectionInterplanetary magnetic fieldElectric fieldAtmospheric sciencesNorthern HemisphereAltitude (triangle)GeophysicsLatitudeGeodesyMagnetic fieldSolar windGeologyMeteorologyAstronomyGeometry

Abstract

fetched live from OpenAlex

An analysis of the electron density measurements (Ne) along the flyby trajectories over the high-latitude region of the Northern Hemisphere under winter conditions in 2014 and 2016 has shown that the main large-scale structure observed by Swarm satellites is the tongue of ionization (TOI). At the maximum of the solar cycle (F10.7 = 160), the average value of Ne in the TOI region at an altitude of 500 km was 8 × 104 cm–3. Two years later, at F10.7 = 100, Ne ~ 5 × 104 cm–3 and Ne ~2.5 × 104 cm–3 were observed at altitudes of 470 and 530 km, respectively. During the dominance of the azimuthal component of the interplanetary magnetic field, the TOI has been observed mainly on the dawn or dusk side depending on the sign of B y . Simultaneous observations of the convective plasma drift velocity in the polar cap show the transpolar flow drift to the dawn (By < 0) or dusk side (B y < 0). Observations and numerical simulation of the Ne distribution have confirmed the significant role of the electric field of the magnetospheric convection in the generation of large-scale irregularities in the polar ionosphere.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.462
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0030.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.355
Teacher spread0.290 · 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.

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

Citations2
Published2017
Admission routes1
Has abstractyes

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