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Record W2510037958 · doi:10.1109/antem.2016.7550165

SIW magic tee fed by printed Ridge Gap Waveguide design

2016· article· en· W2510037958 on OpenAlexaff
Shoukry I. Shams, Mohamed A. Abdelaal, Ahmed A. Kishk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsBandwidth (computing)MAGIC (telescope)Magic teeWaveguideComputer scienceElectronic engineeringElectrical engineeringEngineeringMaterials scienceTelecommunicationsOptoelectronicsPhysicsPower dividers and directional couplers

Abstract

fetched live from OpenAlex

Magic Tee is a four port passive device presented more than 50 years ago. It is deployed in many applications such as duplexers and antenna feeding structures. This type of devices is developed and implemented through different guiding structures. Two major modern guiding structures are the Substrate integrated waveguide (SIW) and the Ridge Gap Waveguide (RGW). This paper introduces a compact magic Tee design implemented by a mixed technology of SIW and RGW. The traditional magic tee contains three ports in one plane, while the fourth port exists in another plane. This results in a large size of the complete structure. This work proposes mixing two different guiding structures in one design in order to overcome this problem. The final results of the magic Tee with the RGW transition shows a good matching and isolation levels for the required bandwidth.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 integrity0.0010.000
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 head0.017
GPT teacher head0.204
Teacher spread0.187 · 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

Citations10
Published2016
Admission routes1
Has abstractyes

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