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Record W2513153855 · doi:10.1088/0963-0252/25/5/055007

Characterization of magnetically confined low-pressure plasmas produced by an electromagnetic field in argon-acetylene mixtures

2016· article· en· W2513153855 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePlasma Sources Science and Technology · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicDust and Plasma Wave Phenomena
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche Scientifique
KeywordsAcetylenePlasmaArgonIonChemistryNucleationAtomic physicsAtmospheric pressureNoble gasPlasma parametersAnalytical Chemistry (journal)Organic chemistry

Abstract

fetched live from OpenAlex

Dust particles formation was investigated in magnetically confined low-pressure plasma produced in argon-acetylene mixtures. The plasma characteristics were measured in order to identify the species involved in the dust particles formation. Their dependence on the operating conditions including magnetic field intensity, acetylene fraction in the gas mixture and operating pressure was examined. In contrast with noble gases, in the presence of acetylene, the electron temperature increases with the magnetic field intensity, indicating additional charged particles losses in the plasma. Indeed, in these conditions, larger hydrocarbon ions are produced leading to the formation of dust particles in the plasma volume. The observed dependence of positive ion mass distribution and density and relative negative ion density on the operating parameters suggests that the dust particles are formed through different pathways, where negative and positive ions are both involved in the nucleation.

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.

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 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 score0.027
Threshold uncertainty score0.452

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.003
GPT teacher head0.193
Teacher spread0.189 · 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