MétaCan
Menu
Back to cohort

Use of 3D field simulators in the synthesis of waveguide capacitive iris coupled lowpass filters

2000· article· en· W2061394922 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsCapacitive sensingBand-pass filterWaveguide filterWaveguideLow-pass filterFilter (signal processing)Electromagnetic fieldFinite element methodDiscontinuity (linguistics)Computer scienceElectronic engineeringAcousticsPrototype filterMathematicsEngineeringPhysicsOpticsElectrical engineeringMathematical analysis

Abstract

fetched live from OpenAlex

This paper presents the generalized lowpass filter design method of Levy based on three-dimensional electromagnetic analysis and discontinuity modeling using commercially available full-wave electromagnetic simulators. It shows how to use Levy's method for very accurate theoretical design of a waveguide capacitive iris lowpass filter, using modern 3D EM field-solvers based on the finite element method (FEM), the mode matching method (MM), and the transmission line matrix (TLM) analysis method. This is the first time that design curves and equations, based on full electromagnetic modeling, have been presented for constant thickness capacitive iris filters. We will demonstrate our approach by designing a number of waveguide capacitive iris filters. This paper also demonstrates the generality of the method. This method can be applied to many other types of waveguide lowpass and bandpass filters. © 2000 John Wiley & Sons, Inc. Int J RF and Microwave CAE 10: 190–198, 2000.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.741

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.206
Teacher spread0.196 · 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