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Record W1987957935 · doi:10.1029/2010ja015410

Modeling ULF waves in a compressed dipole magnetic field

2010· article· en· W1987957935 on OpenAlexaff
A. W. Degeling, R. Rankin, К. Кабин, I. J. Rae, F. R. Fenrich

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMagnetosphereMagnetopausePhysicsGeophysicsMagnetohydrodynamicsRing currentComputational physicsEarth's magnetic fieldField lineDipoleSolar windMagnetosheathAlfvén waveUltra low frequencyMagnetic fieldAcoustics

Abstract

fetched live from OpenAlex

This paper presents the results of a linear model for global scale magneto‐hydrodynamic (MHD) waves in a compressed dipole model magnetosphere. We examine scenarios where a localized monochromatic source along the magnetopause boundary launches MHD fast mode ultralow frequency (ULF) waves into the magnetosphere, where they couple to shear Alfvén waves. Sharply peaked field line resonance (FLR) structures are found to form at discrete locations within the magnetosphere in response to the fast mode driver. The extent in local time and relative amplitudes of FLR structures are found to depend strongly on the source location along the magnetopause boundary, indicating how the addition of day/night asymmetry affects the penetration of MHD fast waves within the magnetosphere. This also suggests that observed FLR structures within the magnetosphere may be used to deconvolve the spatial characteristics of the ULF wave source at the magnetopause, giving insight to the excitation mechanism responsible for observed ULF waves. As an example, we consider narrow band ULF activity observed on 25 November 2001 during a high solar wind speed interval following a geomagnetic storm and qualitatively reproduce the spatial and temporal characteristics of observations made by the Prince George SuperDARN radar by constraining the ULF wave source characteristics.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.998

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 communication0.0000.000
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 head0.016
GPT teacher head0.302
Teacher spread0.285 · 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 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

Citations55
Published2010
Admission routes1
Has abstractyes

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