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Record W1992660755 · doi:10.1063/1.2037873

Kinetics driving high-density chlorine plasmas

2005· article· en· W1992660755 on OpenAlexafffund
Luc Stafford, J. Margot, François Vidal, Mohamed Chaker, Karl Giroux, Jean-Sébastien Poirier, Antoine Quintal-Léonard, J. Saussac

Bibliographic record

VenueJournal of Applied Physics · 2005
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsDissociation (chemistry)ChlorinePlasmaCharged particleKineticsChemistryAtomic physicsMoleculeChemical kineticsChemical physicsIonPhysicsPhysical chemistryNuclear physicsClassical mechanics

Abstract

fetched live from OpenAlex

A simple fluid model was developed in order to investigate the driving kinetics of neutral and charged species in high-density chlorine plasmas. It was found that the dissociation degree of Cl2 molecules is directly linked to the power balance of the discharge which controls the electron density. The model was also used to identify those reactions that could be neglected in the particle balance of charged species and those that must be included. Our results further indicate that diffusion losses need to be considered up to a pressure that depends on magnetic-field intensity and reactor aspect ratio. Finally, it is shown that the dominant charged carriers are linked to the dissociation level of Cl2 molecules.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.191
Teacher spread0.185 · 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

Citations23
Published2005
Admission routes2
Has abstractyes

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