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Record W2040081989 · doi:10.1029/2009gl039985

Modeling EMIC wave growth during the compression event of 29 June 2007

2009· article· en· W2040081989 on OpenAlexaboutno aff
J. P. McCollough, S. R. Elkington, D. N. Baker

Bibliographic record

VenueGeophysical Research Letters · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEmic and eticEvent (particle physics)Compression (physics)GeologySeismologyGeodesyPhysicsAstrophysicsThermodynamics

Abstract

fetched live from OpenAlex

On 29 June 2007, EMIC waves were observed on the ground by the Canadian Array for Realtime Investigations of Magnetic Activity (CARISMA) network of magnetometers between L = 5 and L = 7 in response to a significant magnetospheric compression. We describe a new MHD/particle method to simulate the phase space density dynamics of warm plasma particles in a realistic magnetosphere from the global Lyon‐Fedder‐Mobarry (LFM) MHD code and 3D test‐particle trajectories. We use these results to compute temperature anisotropies and plasma densities. We then compute convective wave growth rates for this event over a range of frequencies, and thus create a spatio‐temporal picture of where waves can be expected to be seen in magnetic local time and L‐shell. Results are shown to be consistent with ground‐based observations of this event.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.282
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations35
Published2009
Admission routes1
Has abstractyes

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