MétaCan
Menu
Back to cohort
Record W2581610770 · doi:10.1109/tmtt.2017.2650230

Printed Texture With Triangle Flat Pins for Bandwidth Enhancement of the Ridge Gap Waveguide

2017· article· en· W2581610770 on OpenAlexaff
Shoukry I. Shams, Ahmed A. Kishk

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsConcordia University
Fundersnot available
KeywordsBandwidth (computing)FabricationOpticsStopbandBroadbandMaterials scienceElectronic engineeringEngineeringAcousticsTelecommunicationsPhysicsBand-pass filter

Abstract

fetched live from OpenAlex

Lately, there has been a growing interest in the ridge gap waveguide (RGW) technology as a guiding structure for high-frequency applications. Low loss and low dispersion are two major advantages of the RGW. On the other hand, the major disadvantage of this technology is the difficulty in fabrication as it requires fabrication with high precision, in particular for high-frequency applications. The operating bandwidth of the RGW is controlled by the stopband of the texture surrounding the ridge. A study to enhance the bandwidth is introduced for possible utilization of the full band achievable by the unit cell in the presence of the ridge. Modifications of the cell filling shape and the ridge structure are carried out to enhance the RGW bandwidth. We have introduced a new RGW based on mixed fabrication technology. The proposed architecture introduces adaptive and straightforward structure with improved bandwidth while keeping the characteristic impedance at the same value. The proposed structure is fabricated and measured. The measured scattering parameters are in excellent agreement with the simulated ones.

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 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.911
Threshold uncertainty score0.662

Codex and Gemma teacher scores by category

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

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 head0.012
GPT teacher head0.235
Teacher spread0.223 · 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 teacher head, 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

Citations22
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Microwave Theory and TechniquesSame topicMicrowave Engineering and WaveguidesFrench-language works237,207