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Record W2044732500 · doi:10.1002/2014ja020387

Multiscale equatorial electrojet turbulence:Baseline 2‐D model

2015· article· en· W2044732500 on OpenAlexaff
Ehab Hassan, W. Horton, A. I. Smolyakov, D. R. Hatch, S. K. Litt

Bibliographic record

VenueJournal of Geophysical Research Space Physics · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Saskatchewan
FundersU.S. Naval Research LaboratoryAin Shams UniversityUniversity of Texas at AustinNational Science Foundation
KeywordsPhysicsPlasmaElectrojetComputational physicsElectric fieldInstabilityTurbulenceElectronAtomic physicsMechanicsMagnetic fieldEarth's magnetic fieldQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract The spatial and spectral characteristics of the turbulent plasma density, electric fields, and ion drift in ionospheric E region are studied using a new set of nonlinear plasma fluid equations. The fluid model combines both Farley‐Buneman (Type‐I) and Gradient‐Drift (Type‐II) plasma instabilities in the equatorial electrojet. In our unified model of the plasma instabilities, we include the ion viscosity in the ion momentum equation and electron inertia in the electron momentum equation. These two terms play an important role in stabilizing the growing modes in the linear regime and in driving the Farley‐Buneman instability into the saturation state. The simulation results show good agreements with a number of features of rocket and radar observations, such as (1) saturation of plasma density perturbations depends on the solar condition and reaches 7–15% relative to the background, (2) fluctuation of the horizontal secondary electric field reaches 8–15 mV/m, (3) stabilization of the phase velocity of the perturbed density wave around the value of the ion‐acoustic speed inside the electrojet, (4) “up‐down” asymmetry in the vertical fluxes of the plasma density, (5) “east‐west” asymmetry of the plasma zonal drifts, and (6) generation of small scale of the order of meter scale lengths irregularities embedded in large‐scale structures. Spectral analysis of the density fluctuations reveals the energy cascade due to the nonlinear coupling between structures of different scales. The break‐up of the large‐scale structures into small‐scale structures explains the disappearance of Type‐II echoes in the presence of Type‐I instabilities.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.051
GPT teacher head0.348
Teacher spread0.297 · 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 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

Citations17
Published2015
Admission routes1
Has abstractyes

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