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Record W4231643970 · doi:10.1002/mmce.20303

Tuning-aided implicit space mapping

2008· article· en· W4231643970 on OpenAlexafffund
Qingsha S. Cheng, J.W. Bandler, José E. Rayas‐Sánchez

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSpace mappingMicrowaveConvergence (economics)ISM bandBand-stop filterSensitivity (control systems)Filter (signal processing)Space (punctuation)Computer scienceMicrostripCADElectronic engineeringTopology (electrical circuits)AlgorithmLow-pass filterEngineeringElectrical engineeringTelecommunicationsEngineering drawingWireless

Abstract

fetched live from OpenAlex

We demonstrate an implicit space mapping (ISM) method for microwave filter design that is enhanced and assisted by a tuning procedure. This procedure helps us to select design variables as well as suitable preassigned parameters for an ISM implementation. It also aids us in the convergence of our ISM algorithm. We investigated and solved a microstrip notch filter using this technique. This shows that tuning-aided sensitivity analysis guides the parameter selections and enhances the performance of ISM optimization. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2008.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.197
Teacher spread0.186 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations27
Published2008
Admission routes2
Has abstractyes

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