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Record W1974049348 · doi:10.1029/2010ja015393

Physical mechanisms of compressional EMIC wave growth

2010· article· en· W1974049348 on OpenAlexaffabout
J. P. McCollough, S. R. Elkington, Maria Usanova, I. R. Mann, D. N. Baker, Z. C. Kale

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMagnetospherePlasmaspherePhysicsGeophysicsComputational physicsEmic and eticMagnetohydrodynamicsEvent (particle physics)CyclotronIonAstrophysicsPlasmaNuclear physics

Abstract

fetched live from OpenAlex

On 29 June 2007, electromagnetic ion cyclotron (EMIC) waves were observed on the ground by the Canadian Array for Realtime Investigations of Magnetic Activity (CARISMA) network of magnetometers between L = 4 and L = 6 in response to a significant magnetospheric compression. Here a new MHD/particle method for studying EMIC wave growth in the magnetosphere is used to provide a detailed study of the compression event. We compare equatorial field line crossings of NASA's Time History of Events and Macroscale Interactions during Substorms (THEMIS) spacecraft and CARISMA observation sites to frequency‐integrated wave growth rates from the MHD/particle method. Simulated temperatures were constant in time, suggesting an absence of energizing processes during this event. Many particles experienced so‐called Shabansky orbits during this event, in which their drift motion was confined to high latitudes in the dayside magnetosphere. We propose a new nonenergizing process, driven by ions undergoing Shabansky orbits, for generating ion temperature anisotropies. In addition, the fundamental role of the plasmasphere in generating EMIC waves from the free energy of warm ion temperature anisotropies is discussed.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.322
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.300
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.

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

Citations98
Published2010
Admission routes2
Has abstractyes

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