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Record W107738854 · doi:10.1063/1.2404565

Generation of Geodesic Acoustic Modes in ITG turbulence

2006· article· en· W107738854 on OpenAlexaff
G. Falchetto, X. Garbet, M. Ottaviani, A. Smolyakov

Bibliographic record

VenueAIP conference proceedings · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhysicsTokamakTurbulenceHarmonicsPlasmaComputational physicsCurvatureGeodesicCoupling (piping)Heat fluxMechanicsQuantum electrodynamicsClassical mechanicsHeat transferQuantum mechanics

Abstract

fetched live from OpenAlex

The generation of geodesic acoustic modes (GAM) is studied by means of numerical simulations of a 3D fluid global model, describing flux‐driven electrostatic ITG (Ion Temperature Gradient) turbulence in the core of tokamak plasmas. The model evolves the equilibrium and the perturbed fields as a whole. The coupling of poloidal harmonics induced by the curvature thus results in the presence of both turbulent and neoclassical transport effects in the system. The neoclassical thermal conductivity, which is linked to the time‐independent component of the poloidal modulation of the equilibrium fields, is observed to be of the order of the turbulent one, in a system driven by strong injected heat fluxes. The frequency spectrum of the electrostatic potential fluctuations exhibits a peak near the theoretical GAM frequency. In the turbulent stationary state of the simulations a downshift of the GAM frequency is observed.

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 score0.003
Threshold uncertainty score0.006

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 studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.034
GPT teacher head0.266
Teacher spread0.232 · 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

Citations1
Published2006
Admission routes1
Has abstractyes

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