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Record W2037461520 · doi:10.1063/1.4885112

Dynamics of multiple double layers in high pressure glow discharge in a simple torus

2014· article· en· W2037461520 on OpenAlexfundno aff
Manash Kumar Paul, P. K. Sharma, Aishwarya Linesh Thakur, S. V. Kulkarni, D. Bora

Bibliographic record

VenuePhysics of Plasmas · 2014
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsnot available
FundersInstitute of Circulatory and Respiratory Health
KeywordsToroidPhysicsPlasmaAnodeGlow dischargeTorusAtomic physicsArgonMagnetic fieldMechanicsElectrodeGeometry

Abstract

fetched live from OpenAlex

Parametric characterization of multiple double layers is done during high pressure glow discharge in a toroidal vessel of small aspect ratio. Although glow discharge (without magnetic field) is known to be independent of device geometry, but the toroidal boundary conditions are conducive to plasma growth and eventually the plasma occupy the toroidal volume partially. At higher anode potential, the visibly glowing spots on the body of spatially extended anode transform into multiple intensely luminous spherical plasma blob structures attached to the tip of the positive electrode. Dynamics of multiple double layers are observed in argon glow discharge plasma in presence of toroidal magnetic field. The radial profiles of plasma parameters measured at various toroidal locations show signatures of double layer formation in our system. Parametric dependence of double layer dynamics in presence of toroidal magnetic field is presented here.

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 score0.001
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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.207
Teacher spread0.200 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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