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Wideband Directional Coupling Structures Based on Ridge Gap Waveguide Technology

2025· article· W7139934850 on OpenAlexaff
Mahmoud Gadelrab, Shoukry I. Shams, Mahmoud Elsaadany, Ghyslain Gagnon, Abdelrazik Sebak

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsÉcole de Technologie SupérieureConcordia University
Fundersnot available
KeywordsCoupling (piping)WidebandRidgeWaveguidePower dividers and directional couplers

Abstract

fetched live from OpenAlex

Directional couplers play a crucial role in microwave and millimeter-wave systems by enabling precise directive sampling while maintaining key performance requirements such as wide bandwidth and flat coupling. Multi-hole couplers, which feature two inline waveguides coupled through their broad or narrow walls, are commonly used to achieve wide bandwidth, flat coupling, and high directivity. Crossguide directional couplers are another widely used configuration in measurement applications. Crossguide directional couplers offer a more compact solution and are easy to manufacture. These features promote the aforementioned topologies in a wide range of applications. However, high-frequency operation introduces several challenges, particularly in waveguide structures where maintaining proper electrical contact is crucial. Moreover, printed structure implementations of directional couplers suffer from high insertion losses, which can significantly impact system efficiency. Addressing these challenges requires an alternative host guiding structure to enhance performance while maintaining compactness and manufacturability.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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