Bibliographic record
Abstract
This simulation study involved the use of a QC-SSIR (quad cross-tub stepped impedance resonator) to examine the behavior and performance of the MW-BPF (multi-wideband band pass filter). To evaluate the performance of the proposed model, it was compared to the case of the conventional resonator. In the results, MW-BPF was found o exhibit a superior performance in terms of the ease of fabrication, good transmission coefficients, and a wider fractional bandwidth. For the filter structure analysis, this study incorporated the ABCD matrix, with the design of the MW-BPF also based on the FR4 microstrip. The experimental conditions and parameters were set in such a way that for the substrate, tan = 0.0265, thickness = 1.6 mm, and r = 4.4, and thickness h = 1.6 mm. at 2.58GHz, 1.71 GHz, and 0.81 GHz, the proposed QC-SSIR-based MW-BPF achieved transmission coefficients/fractional bandwidths of 1.93dB/13.9%, 1.49dB/18.7%, and 0.60dB/49.3%, respectively. Relative to the filter size reduction, the FQC-SSIR (folded quad cross-tub impedance resonator) was incorporated. The resultant observations indicated a possibility of BPF size reduction up to 46%. Also, the proposed framework was found to yield (at 2.62, 1.80, and 0.82 GHz) 1.76dB/12.5%, 1.21dB/17.7%, and 0.57dB/49.6% transmission coefficient/fractional bandwidths, respectively. It is also worth indicating that the filter employed LTE2600, WCDMA1800, and GSM800.
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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 | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".