Bibliographic record
Abstract
The paper presents a new concept for implementing tunable lowpass filters by employing slot resonators etched in the ground plane. When RF MEMS switches are used to short-circuit the slots in the ground plane, the effective length of the slots can be varied to achieve tunability at discrete frequencies. The concept is demonstrated by considering 4-slot lowpass filters. Continuous tuning is achieved by replacing switches with varactors as tuning elements. A varactor tuned lowpass filter was built and tested. Simple transmission line models for the proposed structure are also presented. The measured results are in good agreement with simulations confirming the validity of the proposed model. The experimental lowpass filters exhibit superior RF performance which consists of a low insertion loss and a large tuning range. The insertion loss is 0.6 dB for both the digital and the analogue tunable filters, while the achievable tuning range is 44% for the digital tunable filter and 22% for the analogue tunable filter. A much wider tuning range is obtained by combining digital and analogue tuning in one circuit.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".