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Record W2009241923 · doi:10.1029/2003ja010151

Modeling the properties of guided poloidal Alfvén waves with finite asymmetric ionospheric conductivities in a dipole field

2004· article· en· W2009241923 on OpenAlexaff
L. G. Ozeke, I. R. Mann

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysicsIonosphereComputational physicsWavelengthDipoleElectric fieldMagnetic fieldAlfvén waveHarmonicField lineQuantum electrodynamicsGeophysicsCondensed matter physicsMagnetohydrodynamicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

Analytical and numerical solutions to the guided poloidal Alfvén wave equation in a dipole field are developed, including the effects of realistic and asymmetric finite ionospheric conductivities. We show that when the ionospheric Pedersen conductivity in one hemisphere is less than a critical value, then quarter‐wavelength harmonic modes become possible. We present solutions using realistic plasma density variations along the field line and illustrate how the electric and magnetic fields of a field‐aligned half‐wavelength harmonic mode change as the ionospheric conductivities are made increasingly asymmetric and the wave develops into a quarter‐wavelength mode. Further, we show how over a small critical range of ionospheric Pedersen conductivities, the wave damping rates and frequencies change rapidly as this transition from half‐ to quarter‐wavelength mode occurs. We also show that the phase difference between the electric and magnetic field components is strongly dependent upon the distance along the magnetic field line, upon the asymmetry in the ionospheric Pedersen conductivities, and significantly upon which hemisphere has its footprint in the ionosphere whose conductivity is close to critical. This has important implications for inferring the field‐aligned harmonic mode of standing ULF pulsations when using single satellite data.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.995

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 science0.0010.000
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 head0.035
GPT teacher head0.290
Teacher spread0.255 · 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 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

Citations34
Published2004
Admission routes1
Has abstractyes

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