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Record W4226177554 · doi:10.1029/2021ja030102

Ionospheric Energy Input in Response to Changes in Solar Wind Driving: Statistics From the SuperDARN and AMPERE Campaigns

2022· article· en· W4226177554 on OpenAlexafffund
Daniel Billett, K. A. McWilliams, G. W. Perry, L. B. N. Clausen, B. J. Anderson

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIonosphereMagnetospherePhysicsInterplanetary magnetic fieldGeophysicsSolar windPoynting vectorEarth's magnetic fieldAtmospheric sciencesComputational physicsPlasmaMagnetic field

Abstract

fetched live from OpenAlex

Abstract For over a decade, the Super Dual Auroral Radar Network and the Active Magnetosphere and Planetary Electrodynamics Response Experiment have been measuring ionospheric convection and field‐aligned currents in the high‐latitude regions, respectively. Using both, high‐latitude maps of the magnetosphere‐ionosphere energy transfer rate (the Poynting flux) have been generated with a time resolution of 2 min between 2010 and 2017. These data driven Poynting flux (PF) patterns are used in this study to perform a superposed epoch analysis of the northern hemisphere ionospheric response to transitions of the interplanetary magnetic field B z component, upwards of 60° geomagnetic latitude. We discuss the difference in the distribution of PF between the magnetosphere‐ionosphere Dungey cycle “switching on” and “switching off” to solar wind driving, revealing that they are not symmetric temporally or spatially.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.016
GPT teacher head0.284
Teacher spread0.269 · 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

Citations18
Published2022
Admission routes2
Has abstractyes

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