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Record W4413120422 · doi:10.1109/lmwt.2025.3595425

Quarter-Wavelength Coaxial Stepped Impedance Resonators With Inverted Geometry for High-Power Space Bandpass Filters

2025· article· en· W4413120422 on OpenAlexaff
Alejandro Buitrago Bernal, Jessica Bénédicto, Jean‐François Favennec, Ying Wang, Éric Rius

Bibliographic record

VenueIEEE Microwave and Wireless Technology Letters · 2025
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsBand-pass filterCoaxialResonatorOpticsElectrical impedanceWavelengthAcousticsPower (physics)Materials sciencePhysicsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

This letter presents a novel geometrical implementation of the quarter-wavelength coaxial stepped impedance resonator (SIR). Based on the inversion of the location of the coaxial sections in the resonator, this topology increases the distance between conductors, thus improving the multipactor threshold and fabrication tolerances. To demonstrate these advantages, we designed an L-band 4th-order filter. This filter was fabricated in aluminum and measured. The experimental results are presented and compared with their two- and three-section quarter-wavelength counterparts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.003
GPT teacher head0.186
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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