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Record W3019066037 · doi:10.1002/mop.32398

<scp>Ultra‐wideband</scp> fluidically steered antipodal Vivaldi antenna array

2020· article· en· W3019066037 on OpenAlexafffund
Ian Goode, Carlos E. Saavedra

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsQueen's University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVivaldi antennaBeamwidthAntipodal pointBeam steeringMaterials scienceMicrostripOpticsWidebandAntenna (radio)Antenna arrayPhase (matter)Phase shift moduleBeam (structure)OptoelectronicsPhysicsElectrical engineeringAntenna measurementEngineeringInsertion lossMathematics

Abstract

fetched live from OpenAlex

Abstract An ultra‐wideband 1 × 4 antipodal Vivaldi antenna array with microfluidic beam steering is reported. The antipodal configuration is selected for its microstrip feed line, which is convenient for implementation of the phase‐shifting structure. Each antenna element uses a true‐time‐delay phase shifter consisting of nine microfluidic channels under its feed line in which deionized (DI) water, ɛ r = 77 + j13 (tanδ = 0.17) at 3 GHz, is pumped to change the speed of the propagating wave. The array was fabricated using a 1.52 mm thick substrate with ɛ r = 3.55 and tanδ = 0.0027. Each antenna element and phase shifter measures 55 mm × 140 mm. Measurements show that the array yields up to 90° of beam steering from 3 to 6.5 GHz and up to 40° of steering from 6.5 to 10 GHz. The array has a maximum realized gain of 13.1 dBi, and a half‐power beamwidth of less than 40° for all configurations.

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 score0.004

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 science0.0010.000
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 head0.008
GPT teacher head0.184
Teacher spread0.176 · 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

Citations11
Published2020
Admission routes2
Has abstractyes

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