MétaCan
Menu
Back to cohort
Record W4383376470 · doi:10.1029/2022rs007623

A Novel Low‐Loss Planar PRGW Crossover Design for 5G Applications

2023· article· en· W4383376470 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRadio Science · 2023
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia UniversityInstitut National de la Recherche ScientifiqueUniversité du Québec à Montréal
FundersInstitut national de la recherche scientifique
KeywordsCrossoverPlanarBandwidth (computing)Return lossInsertion lossExtremely high frequencyMillimeterComputer scienceOpticsMaterials scienceTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Abstract In this paper, a planar 0‐dB crossover using printed ridge gap waveguide (PRGW) technology is proposed and designed for millimeter‐wave applications. PRGW as a quasi‐TE mode is considered as the modern guiding technology at high frequencies and for the 5G and other upcoming communications. A prototype of the proposed PRGW crossover working around 30 GHz is fabricated and measured to validate the simulated results. Comparing simulated with measured results, a good agreement is observed. The measured results demonstrate that the designed crossover offers an insertion loss of better than 0.5 dB over the whole operating frequency bandwidth from 29 to 31 GHz where the return loss level is better than 15 dB and the isolation level is less than −13 dB. Compared with the other reported crossover structures, the designed PRGW crossover features a wider bandwidth with a smaller and planar configuration.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: none
Teacher disagreement score0.958
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.023
GPT teacher head0.247
Teacher spread0.224 · 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