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Record W2063708499 · doi:10.1063/1.2203235

Generation of zonal flows by ion-temperature-gradient and related modes in the presence of neoclassical viscosity

2006· article· en· W2063708499 on OpenAlexaff
A. B. Mikhaǐlovskiǐ, A. I. Smolyakov, E. A. Kovalishen, M. S. Shirokov, V. S. Tsypin, R. M. O. Galvão

Bibliographic record

VenuePhysics of Plasmas · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhysicsZonal flow (plasma)Nonlinear systemPressure gradientIonMechanicsComputational physicsToroidTemperature gradientConvectionClassical mechanicsElectron temperatureAtomic physicsPlasmaQuantum mechanics

Abstract

fetched live from OpenAlex

Generation of zonal flows by primary waves that are more complex than those considered in the standard drift-wave model is studied. The effects of parallel ion velocity and ion perturbed temperature and the part of the nonlinear mode interaction proportional to the ion pressure are taken into account. This generalization of the standard model allows the analysis of generation of zonal flows by a rather wide variety of primary modes, including ion temperature gradients, ion sound, electron drift, and drift-sound modes. All the listed effects, which are present in the slab geometry model, are complemented by effects of neoclassical viscosity inherent to toroidal geometry. We show that the electrostatic potential of secondary small-scale modes is expressed in terms of a nonlinear shift of the mode frequency and interpret this shift in terms of the perpendicular and parallel Doppler, nonlinear Kelvin-Helmholtz (KH), and nonlinear ion-pressure-gradient effects. A basic assumption of our model is that the primary modes form a nondispersive monochromatic wave packet. The analysis of zonal-flow generation is performed following an approach similar to that of convective-cell theory. Neoclassical zonal-flow instabilities are separated into fast and slow ones, and these are divided into two varieties. The first of them is independent of the nonlinear KH effect, while the second one is sensitive to it.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.240
Teacher spread0.226 · 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 designBench or experimental
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

Citations5
Published2006
Admission routes1
Has abstractyes

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