Relations between the Medium Composition, Dielectric Properties, and Corona Current
Why this work is in the frame
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Bibliographic record
Abstract
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.
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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 it