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Record W2518566259 · doi:10.1002/2016ja022443

Polar cap patch transportation beyond the classic scenario

2016· article· en· W2518566259 on OpenAlexaff
Qinghe Zhang, J. Moen, M. Lockwood, Ian McCrea, Beichen Zhang, K. A. McWilliams, Qiugang Zong, Shun‐Rong Zhang, J. M. Ruohoniemi, E. G. Thomas, M. W. Dunlop, Ruiyuan Liu, Hongqiao Hu, M. Lester

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Saskatchewan
FundersScience and Technology Facilities CouncilNatural Environment Research CouncilNatural Science Foundation of Shandong ProvinceNational Key Research and Development Program of ChinaChinese Arctic and Antarctic AdministrationNational Aeronautics and Space AdministrationNorges ForskningsrådNational Oceanic and Atmospheric AdministrationSight Research UKNational Science Foundation
KeywordsSubstormInterplanetary magnetic fieldGeophysicsPolarConvectionMagnetosphereGeologyPolar capPhysicsSolar windPlasmaIonosphereMeteorologyAstronomy

Abstract

fetched live from OpenAlex

Abstract We report the continuous monitoring of a polar cap patch, encompassing its creation, and a subsequent evolution that differs from the classic behavior. The patch was formed from the storm‐enhanced density plume, by segmentation associated with a subauroral polarization stream generated by a substorm. Its initial antisunward motion was halted due to a rapidly changing of interplanetary magnetic field (IMF) conditions from strong southward to strong eastward with weaker northward components, and the patch subsequently very slowly evolved behind the duskside of a lobe reverse convection cell in afternoon sectors, associated with high‐latitude lobe reconnection, much of it fading rapidly due to an enhancement of the ionization recombination rate. This differs from the classic scenario where polar cap patches are transported across the polar cap along the streamlines of twin‐cell convection pattern from day to night. This observation provides us new important insights into patch formation and control by the IMF, which has to be taken into account in F region transport models and space weather forecasts.

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 score0.310
Threshold uncertainty score0.454

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 communication0.0000.001
Open science0.0010.000
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 head0.018
GPT teacher head0.294
Teacher spread0.276 · 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

Citations33
Published2016
Admission routes1
Has abstractyes

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