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Record W2949275087 · doi:10.1109/tps.2019.2920311

Transport of Dust Particles in Very Low-Pressure Magnetized Plasma Studied by Rapid Imaging

2019· article· en· W2949275087 on OpenAlexaff
Mathias Rojo, X. Glad, J. L. Briançon, J. Margot, Simon Dap, Richard Clergereaux

Bibliographic record

VenueIEEE Transactions on Plasma Science · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPlasmaAmbipolar diffusionDusty plasmaAtomic physicsElectric fieldPhysicsMagnetic fieldIonDragElectronMagnetic confinement fusionAtmospheric-pressure plasmaMaterials scienceMechanicsTokamakNuclear physics

Abstract

fetched live from OpenAlex

Incandescent dust particles are observed to the naked eye in pure acetylene plasmas excited at electron cyclotron resonance (ECR). Their transport in a plane parallel to the magnets is studied using fast imaging combined with a tracking algorithm. The dynamics of dust particles exhibit specific trends depending on the direction considered within the magnetic field (B⃗), the position in the plasma reactor, and the time after plasma ignition. This transport is discussed considering the electric and the ion drag forces. Although the transport of dust particles is governed by the space-charge electric field in the direction parallel to B⃗, it involves cross-field mechanisms in the direction perpendicular to B⃗ related, specifically, to the ambipolar E⃗ x B⃗ drift as supported by a simple model. However, to fully describe these transport phenomena, one would also consider spatial and time-evolutions of plasma parameters in the dusty plasma.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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 teacher head, not a consensus.

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

Citations2
Published2019
Admission routes1
Has abstractyes

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