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Record W2152646624 · doi:10.1017/s0022377806006027

Magnetic island evolution in rotating plasmas

2006· article· en· W2152646624 on OpenAlexaff
Yasutomo Ishii, M. Azumi, A. I. Smolyakov

Bibliographic record

VenueJournal of Plasma Physics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhysicsMagnetohydrodynamicsMagnetohydrodynamic drivePlasmaTokamakTearingResistive touchscreenRational surfaceElectrical resistivity and conductivityMagnetic fluxMagnetic fieldInstabilityCondensed matter physicsMechanicsThermodynamicsNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

The time evolution of the magnetic island formed at the tearing stable rational surface by the external magnetic flux perturbation in the plasma with poloidal flow is investigated numerically by using the resistive magnetohydrodynamic (MHD) model and the magnetic island is found to show rapid growth after the reduced growth phase due to the plasma rotation. It was also found that the onset condition of this rapid growth depends on the resistivity, but does not depend on the viscosity, in the parameter regime used in this study. On the other hand, the time constant of the rapid growth phase is almost independent of both the plasma resistivity and the viscosity. This rapid growth of magnetic island is the possible candidate for the trigger problem of the neoclassical tearing mode in a tokamak.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.231
Teacher spread0.224 · 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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