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Record W1851489515

Single frequency 2-D leaky-wave beam steering using an array of surface-wave launchers

2009· article· en· W1851489515 on OpenAlexaff
Symon K. Podilchak, A.P. Freundorfer, Yahia M. M. Antar

Bibliographic record

VenueEuropean Conference on Antennas and Propagation · 2009
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsQueen's UniversityRoyal Military College of Canada
Fundersnot available
KeywordsOpticsSurface waveConical surfaceBeam steeringAperture (computer memory)Antenna (radio)ExcitationExtremely high frequencyPlanarPhysicsLeaky wave antennaPhase (matter)Beam (structure)Planar arrayAcousticsMaterials scienceEngineeringMicrostrip antennaElectrical engineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

A planar antenna that utilizes surface-waves (SWs) for leaky-wave (LW) excitation is presented for millimeter-wave applications. Specifically, a two element array of directive Yagi-Uda like surface-wave launchers (SWLs) is used as the antenna feed, exciting cylindrical SWs on a grounded dielectric slab. By varying the relative phase difference between elements, the excited SW field distribution can be controlled. With the addition of metallic circular strip gratings, suitable conditions for LW excitation can be achieved. Essentially cylindrical LWs can be steered to confined regions on the guiding surface. For instance, by changing the relative phase difference between SWL sources such aperture fields can produce pencil and conical-sector beam patterns that can be steered in the far field at a single frequency. To the authors knowledge this is the first time such a LWA has been designed, fabricated and measured.

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: Empirical
Teacher disagreement score0.481
Threshold uncertainty score0.860

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 head0.062
GPT teacher head0.228
Teacher spread0.166 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

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