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Record W2111738909 · doi:10.1109/aps.2006.1711536

A Metamaterial Series-Fed Linear Dipole Array with Reduced Beam Squinting

2006· article· en· W2111738909 on OpenAlexaff
Marco A. Antoniades, George V. Eleftheriades

Bibliographic record

Venue2006 IEEE Antennas and Propagation Society International Symposium · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBroadsideMetamaterialMetamaterial antennaBeam steeringOpticsLeaky wave antennaElectric power transmissionTransmission lineCapacitorSeries (stratigraphy)Dipole antennaPhysicsAntenna (radio)Beam (structure)Materials scienceOptoelectronicsMicrostrip antennaElectrical engineeringComputer scienceTelecommunicationsEngineeringSlot antennaVoltage

Abstract

fetched live from OpenAlex

The recent implementation of negative-refractive-index (NRI) media by periodically loading host transmission-lines (TL) with lumped-element series capacitors and shunt inductors has led to the development of numerous practical devices based on NRI-TL metamaterials (MTM). The MTM feed networks were shown to be useful in series-fed linear arrays for effectively replacing one-wavelength long conventional meandered transmission lines, thus achieving compact, broadside radiators, whose beam squints less with frequency. In addition, the MTM feed networks can be used to create linear arrays whose main beam remains virtually fixed at a negative angle from broadside as the frequency is varied. Alternatively, a single CPS MTM feedline operating inside the radiation cone can be used to implement a leaky-wave antenna (LWA), which can be recognized as the dual of the CPW line to create a backward LWA

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.007
GPT teacher head0.211
Teacher spread0.204 · 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

Citations30
Published2006
Admission routes1
Has abstractyes

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