Bibliographic record
Abstract
A method is established for the analysis of annular slot array antennas loaded with dielectric layers and fed by either radial waveguide or cavity. The analysis is based on the boundary value method. The Greens functions for each region are obtained, and then the induced magnetic current over the slots is expanded into Fourier series with unknown coefficients. Boundary conditions are applied, and a matrix equation for these unknown coefficients is obtained. For narrow slots the number of unknowns equals the number of annular slots, and an extremely rapid solution is obtained. The far-field formulation is derived using the magnetic current on the dielectric layer. The method is confirmed numerically by comparing the simulation results for sample small antennas with a commercial numerical tool (IE3D), and good agreement is achieved. It is shown that adding the dielectric layers can improve the antenna directivity. In comparison with other methods, the proposed method is very efficient, and its computation efforts depend on the number of annular slots and not the size of the antenna. As an example, for a single-slot antenna the number of unknowns to be determined is only one, while in IE3D it is more than 300.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".