Influence of trace additives on dielectric properties of gas
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".