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Record W2775259022 · doi:10.1002/2017ja024644

Interhemispheric Asymmetry of the Sunward Plasma Flows for Strongly Dominant IMF <i>B</i><sub><i>Z</i></sub> &gt; 0

2017· article· en· W2775259022 on OpenAlexaff
K. Yakymenko, A. V. Koustov, Robyn Fiori

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsNatural Resources CanadaUniversity of Saskatchewan
Fundersnot available
KeywordsNoonNorthern HemisphereSouthern HemisphereInterplanetary magnetic fieldGeologyMidnightLatitudePolarIonosphereConvectionPhysicsAtmospheric sciencesGeophysicsGeodesyMagnetic fieldClimatologySolar windMeteorologyAstronomy

Abstract

fetched live from OpenAlex

Abstract Super Dual Auroral Radar Network (SuperDARN) convection maps obtained simultaneously in both hemispheres are averaged to infer polar cap ionospheric flow patterns under strongly dominant positive interplanetary magnetic field (IMF) B z component. The data set consisted of winter observations in the Northern Hemisphere simultaneously with summer observations in the Southern Hemisphere. Long‐lasting high‐latitude dayside reverse convection cells are shown to have faster sunward flows at near‐magnetic noon hours in the summer/Southern Hemisphere. Sunward flows typically deviate from the midnight‐noon meridian toward 10–11 h of magnetic local time in the summer/Southern Hemisphere and are more aligned with the midnight‐noon meridian in the winter/Northern Hemisphere. Flow deviations in the winter/Northern Hemisphere can be both toward prenoon and postnoon hours, and there is no clear relationship between flow deviation and the IMF B y component. No strong preference for the sunward flow occurrence depending on the IMF B x polarity was found. In addition, the rate of the sunward flow speed increase in response to an increase in driving conditions was found to be comparable for the IMF B x &gt; 0 and B x &lt; 0 .

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0020.001
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 head0.019
GPT teacher head0.303
Teacher spread0.284 · 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 designBench or experimental
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
Published2017
Admission routes1
Has abstractyes

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