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Record W2011939798 · doi:10.1109/8.855492

Design and analysis of multisegment dielectric resonator antennas

2000· article· en· W2011939798 on OpenAlexaff
A. Petosa, N.R.S. Simons, R. Siushansian, A. Ittipiboon, M. Cuhaci

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2000
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsCommunications Research Centre Canada
Fundersnot available
KeywordsMicrostripDielectric resonatorDielectric resonator antennaDielectricMaterials scienceAntenna (radio)Microstrip antennaResonatorElectrical impedancePermittivityCoupling (piping)AcousticsOptoelectronicsElectronic engineeringElectrical engineeringPhysicsEngineeringComposite material

Abstract

fetched live from OpenAlex

The multisegment dielectric resonator antenna (SDRA) has previously been developed to significantly enhance the coupling to a microstrip line. The MSDRA greatly facilitates the integration with a printed feed distribution network for use in a large array environment. The thickness and permittivity of the dielectric insert of the MSDRA can be adjusted to match the element impedance to that of the feed line. A detailed study of the effects of varying the dielectric insert parameters was carried out and useful guidelines are presented for the design of MSDRAs.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.001

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 head0.013
GPT teacher head0.214
Teacher spread0.202 · 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

Citations195
Published2000
Admission routes1
Has abstractyes

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