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Record W2094401127 · doi:10.1109/07ias.2007.172

Relations between the Medium Composition, Dielectric Properties, and Corona Current

2007· article· en· W2094401127 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.

Bibliographic record

VenueConference record · 2007
Typearticle
Languageen
FieldMedicine
TopicPlasma Applications and Diagnostics
Canadian institutionsWestern University
Fundersnot available
KeywordsCorona (planetary geology)Current (fluid)Electric fieldCorona dischargeDielectricVoltageAnalytical Chemistry (journal)Dielectric strengthMaterials scienceBreakdown voltageChemistryOptoelectronicsElectrical engineeringEnvironmental chemistryPhysicsThermodynamics

Abstract

fetched live from OpenAlex

Problems are discussed of the interaction between an inhomogeneous electric field and the species that the field produces in medium, which in the end are recognized as corona current. The work is based on the analysis of voltage-current characteristics, measured in several gas mixtures, created in a special apparatus that allowed handling and controlling the composition to 0.1 ppm. The results were verified using gas chromatographic and spectroscopic techniques. It has been determined that several medium additives, in trace concentrations, have a significant impact on the magnitude of the corona current and the electrical breakdown strength of the medium. Role of the additives in the corona medium is analyzed in terms of their chemical physics properties, and their effectiveness in breakdown suppression. For several electric field intensities and concentrations, the additives are classified according to the impact of their Milliken-Jaffe energy on 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.649
Threshold uncertainty score0.218

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 head0.067
GPT teacher head0.293
Teacher spread0.226 · 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