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Record W2056837111 · doi:10.1109/optim.2010.5510351

Influence of trace additives on dielectric properties of gas

2010· article· en· W2056837111 on OpenAlexafffund
Z. Kucerovsky, Adrian Ieta

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsWestern University
FundersSuncor Energy Incorporated
KeywordsCorona (planetary geology)Current (fluid)Corona dischargeDielectricDielectric strengthElectric fieldVoltageMaterials scienceBreakdown voltageAnalytical Chemistry (journal)Work (physics)ChemistryOptoelectronicsElectrical engineeringEnvironmental chemistryThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Corona current is produced by interactions between an inhomogeneous electric field and gas. In this paper, the impact of the field on the gaseous medium is studied by measuring and analyzing voltage-current characteristics in several gas mixtures. As the work requires strict control of the medium, with mixture compositions guaranteed to ~ 0.1 ppm, the corona is created in a special apparatus that facilitates medium handling. Gas chromatographic and spectroscopic techniques have been used to verify the results. It has been established that several trace concentrations of certain medium additives have a considerable impact on the magnitude of the corona current, and on the electrical dielectric properties and breakdown strength of the medium. Role of the additives in the corona medium is analyzed in terms of their chemical properties and their efficacy in suppressiong the breakdown. The additives, divided into groups according to their Milliken-Jaffe energy, are classified in terms of their impact on the corona current and breakdown.

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 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 score0.006
Threshold uncertainty score0.163

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.196
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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

Citations1
Published2010
Admission routes2
Has abstractyes

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