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Record W2068289629 · doi:10.1088/0004-637x/780/2/144

PROPERTIES OF MAGNETIC HELICITY FLUX IN TURBULENT DYNAMOS

2013· article· en· W2068289629 on OpenAlexaff
Ethan T. Vishniac, Dmitry Shapovalov

Bibliographic record

VenueThe Astrophysical Journal · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsUniversity of Saskatchewan
FundersEusko Jaurlaritza
KeywordsPhysicsDynamoHelicityTurbulenceMagnetic helicitySolar dynamoMagnetic fieldDynamo theoryMagnetohydrodynamic turbulenceAdvectionMagnetic fluxMagnetohydrodynamicsFlux (metallurgy)Classical mechanicsMechanicsQuantum mechanics

Abstract

fetched live from OpenAlex

We study the flux of small-scale magnetic helicity in simulations of driven statistically homogeneous magnetohydrodynamic turbulence in a periodic box with an imposed large-scale shear. The simulations show that in the regime of strong dynamo action the eddy-scale magnetic helicity flux has only two significant terms: advective motion driven by the large-scale velocity field and the Vishniac–Cho (VC) flux which moves helicity across the magnetic field lines. The contribution of all the other terms is negligible. The VC flux is highly correlated with the large-scale electromotive force and is responsible for large-scale dynamo action, while the advective term is not. The VC flux is driven by the anisotropy of the turbulence. We derive analytical expressions for it in terms of the small-scale velocity or magnetic field. These expressions are used to predict the existence and strength of dynamo action for different turbulent anisotropies and tested against the results of the simulations.

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)0.003
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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.007
GPT teacher head0.194
Teacher spread0.187 · 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

Citations25
Published2013
Admission routes1
Has abstractyes

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