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Record W2922427494 · doi:10.1109/access.2019.2904247

Wideband Printed TM<sub>01</sub> to TE<sub>11</sub> Mode Converters

2019· article· en· W2922427494 on OpenAlexafffund
Mohammad Mahdi Honari, Rashid Mirzavand, Samira Aslanzadeh, Hossein Saghlatoon, Pedram Mousavi

Bibliographic record

VenueIEEE Access · 2019
Typearticle
Languageen
FieldPhysics and Astronomy
TopicGyrotron and Vacuum Electronics Research
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology Futures
KeywordsConvertersWidebandBandwidth (computing)Electronic engineeringFabricationMode (computer interface)Computer scienceElectrical engineeringEngineeringOpticsPhysicsTelecommunicationsVoltage

Abstract

fetched live from OpenAlex

Different structures for three categories of the TM01-TE11 mode converters; i.e., dielectric loaded-based, metallic septum-based, and mode converter with intermediate modes; are proposed and investigated for the aim of wider operational bandwidth. The principles of operation of all mode converters are explained in detail. Thanks to 3D printing capabilities, the design can be very flexible and the optimal results are achieved using more complicated structures in an easy and realizable fabrication process. The simulation and measurement results of the proposed TM01-TE11 mode converters, including reflection coefficients and radiation patterns, show great conversion efficiency and wideband performances with fractional bandwidths up to 20.8%.

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 score0.002
Threshold uncertainty score0.007

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 communication0.0010.000
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 head0.019
GPT teacher head0.317
Teacher spread0.298 · 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

Citations22
Published2019
Admission routes2
Has abstractyes

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