Suppression of spurious modes for performance enhancement of hybrid planar∕NRD-guide integrated circuits
Bibliographic record
Abstract
A technique for suppressing spurious modes is presented with experimental and analysis results. It is simple and very effective in rejecting spurious modes for performance enhancement of hybrid planar/NRD-guide integrated circuits. As a practical example, a millimetre–wave planar/NRD-guide filter is designed to evaluate features of the proposed technique, which yields good results. It is found through preliminary analysis and experiments that the rejection of all spurious modes (including TE and LSE modes) can be better than −35 dB for a single microstrip-to-NRD-guide transition over the broadband frequency range of interest, and performance can be further enhanced using optimised design procedures. This new technique provides an alternative solution to the inherent problem of spurious modes occurring (especially TE modes) in the standard NRD-guide circuit design.
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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".