Higher-order structural constraints for improved optimization of nonuniform helical antennas
Why this work is in the frame
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Bibliographic record
Abstract
The objective is to improve the linear constraints for optimizing the helical structure (radius and pitch of the conductor winding) of nonuniform helical antennas for desired characteristics such as signal gain or bandwidth. Presented below are equations that allow various higher-order structural constraints to be used in such optimizations. Their efficacy is demonstrated by analogy, using data for a fully optimized Yagi-Uda antenna, before being applied to data available for helical designs. The comparisons confirm the general validity of the higher-order equations to model some of the most advanced antennas produced to date. A simple calculus-of-variations test confirms that an improved optimization is possible by adding curvature terms to previously published linear constraints.
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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