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Record W3204575048 · doi:10.1109/lawp.2021.3115234

Low-Profile CPW-PS-Fed Magnetoelectric Antenna

2021· article· en· W3204575048 on OpenAlexafffund
Aditya Singh, Carlos E. Saavedra

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2021
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCoplanar waveguideStriplineSTRIPSDipoleStanding wave ratioRadiation patternMaterials scienceOptoelectronicsPhysicsAntenna (radio)Electrical engineeringMicrowaveMicrostrip antennaEngineeringComposite materialQuantum mechanics

Abstract

fetched live from OpenAlex

A magnetoelectric antenna (MEA) that uses coplanar waveguide (CPW)-to-parallel-strip-line transition as feed to obtain a wide bandwidth is presented for millimeter-wave (mm-wave) bands. The balanced feed is utilized to feed a modified magnetoelectric dipole. The modified structure consists of a simple two-metal-strips MEA loaded with metallic loops. The resonant modes study shows that a new resonant mode is contributed by the loop when the loop length is nearly a wavelength, thereby improving the impedance bandwidth (IBW) and realized gain. A prototype is fabricated in-house with printed circuit board technology. Measured results validate a fractional IBW (VSWR$\leq$2) of 75.76% with realized gain being 8.6$\pm$1.8 dBi for 14–29 GHz. The radiation pattern measurements indicate a stable radiation pattern across the band with low broadside cross-polarization levels in both E- and H- planes. The simulated total efficiency is 86–96%.

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 head0.006
GPT teacher head0.186
Teacher spread0.180 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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