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Record W2054974989 · doi:10.1063/1.1472501

Edge plasma density convection during ion cyclotron resonance heating on Tore Supra

2002· article· en· W2054974989 on OpenAlexfundno aff
M. Bécoulet, L. Colas, S. Pécoul, J. Gunn, Ph. Ghendrih, A. Bécoulet, S. Heuraux

Bibliographic record

VenuePhysics of Plasmas · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory Health
KeywordsTore SupraPhysicsPlasmaTokamakAtomic physicsLangmuir probeConvectionAsymmetryCyclotronResonance (particle physics)Antenna (radio)Nuclear magnetic resonancePlasma diagnosticsNuclear physicsMechanics

Abstract

fetched live from OpenAlex

The two-dimensional (2D) edge plasma density distribution in the scrape off layer magnetically connected to the ion cyclotron resonance heating (ICRH) antennae is studied experimentally and numerically in the tokamak Tore Supra. A local density decrease in front of the loaded ICRH antenna (“pump-out” effect) is demonstrated by Langmuir probe measurements in a low recycling regime. An up–down asymmetry in the heat-flux and in the antenna erosion is also observed, and is associated with poloidal variations of the local density. These density redistributions are ascribed to an E×B convection process linked with rf sheaths. To assess this interpretation, the 2D transport code CELLS for modeling the density distribution near an ICRH antenna was developed and described in this paper. The code takes into account perpendicular diffusion, parallel transport and convection in rf-sheath-driven potentials. The strong density differences obtained in simulations reproduce up–down asymmetries of the heat fluxes.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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 studies0.0000.000
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.237
Teacher spread0.219 · 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 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

Citations77
Published2002
Admission routes1
Has abstractyes

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