Calorimetric calibration of spark gaps for electrostatic discharge studies
Bibliographic record
Abstract
Spark gaps are convenient sources of electromagnetic energy, that are used for studying interactions of systems with electrostatic discharge and the electromagnetic pulse. The authors' study focuses on the optical emission of the spark gap, which is used as a source of electromagnetic energy for studying electrostatic discharge and the electromagnetic energy pulse. The goal of their work is to measure the spark gap's energy, contained in the optical and quasi optical regions. A reasonably simple and inexpensive method is developed for measuring the spark plug energy, which yields the value of spark plug energy in fundamental units, and which does not require complicated calibration. A spark plug signal generator and the associated apparatus are developed, suitable for industrial environment. A high sensitivity calorimeter is used for the determination of the energy contained in the spark plug optical emission. The long-term stability of the system was found to be acceptable and the system suitable for the nonintrusive characterization of optical emissions.
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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 | 0.001 |
| 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".