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Record W3037943858 · doi:10.1002/mmce.20401

Computer-aided design and analysis of dielectric resonator antennas

2009· article· en· W3037943858 on OpenAlexaff
Alexandre Perron, Tayeb A. Denidni, A. Sebak

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsConcordia UniversityInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsResonatorDielectric resonator antennaDielectric resonatorMicrowaveDielectricAntenna (radio)Ring (chemistry)Computer Aided DesignAcousticsEngineeringElectronic engineeringElectrical engineeringMaterials sciencePhysicsTelecommunicationsMechanical engineeringChemistry

Abstract

fetched live from OpenAlex

In this article, a freeware tool for computer-aided design and analysis (resonant frequency and unloaded Q-factor) of dielectric resonators for antenna applications is presented. Several resonator shapes, including hemispherical, cylindrical, cylindrical ring, and rectangular cross-section, are supported. © 2009 Wiley Periodicals, Inc. Int J RF and Microwave CAE 2010.

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)0.001
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: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.008
GPT teacher head0.207
Teacher spread0.198 · 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
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

Citations8
Published2009
Admission routes1
Has abstractyes

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