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Record W2586114899 · doi:10.1063/1.4975189

Electromagnetic electron temperature gradient driven instability in toroidal plasmas

2017· article· en· W2586114899 on OpenAlexafffund
J. J. Zielinski, A. I. Smolyakov, Peter Beyer, S. Benkadda

Bibliographic record

VenuePhysics of Plasmas · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsUniversity of Saskatchewan
FundersCampus FranceNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsInstabilityPhysicsPlasmaToroidElectronTemperature gradientGyrokineticsMagnetic fieldElectron temperatureAtomic physicsTwo-stream instabilityWavelengthQuantum electrodynamicsMechanicsCondensed matter physicsComputational physicsTokamakOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

The fluid theory of a new type of electron temperature gradient instability is proposed. This mode is closely related to the short wavelength Alfvén mode in the regime k⊥2ρi2>1. Contrary to standard electron temperature gradient modes, which are mostly electrostatic, the considered mode is fundamentally electromagnetic and does not exist in the electrostatic limit. The mechanism of instability relies on gradients in both the electron temperature and magnetic field. It is suggested that this instability may be a destabilizing mechanism for collisionless microtearing modes, which are observed in a number of gyrokinetic 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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.011
GPT teacher head0.261
Teacher spread0.251 · 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

Citations13
Published2017
Admission routes2
Has abstractyes

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