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Record W2013034976 · doi:10.1109/aps.2006.1710543

Some antenna applications of negative-refractive-index transmission-line (NRI-TL) metamaterials

2006· article· en· W2013034976 on OpenAlexaff
George V. Eleftheriades, Marco A. Antoniades, F. Qureshi

Bibliographic record

Venue2006 IEEE Antennas and Propagation Society International Symposium · 2006
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMetamaterialMetamaterial antennaCapacitorTransmission lineMicrowavePlanarElectric power transmissionPermittivityOptoelectronicsInductorElectronic circuitPhysicsAntenna (radio)Computer scienceElectrical engineeringDirectional antennaTelecommunicationsSlot antennaDielectricEngineeringVoltage

Abstract

fetched live from OpenAlex

Metamaterials are artificial structures engineered to exhibit unusual electromagnetic properties. Metamaterials (MTM) that exhibit a simultaneously negative electric permittivity epsi and magnetic permeability mu, and thus a negative refractive index (NRI), have recently attracted considerable attention in the electromagnetic community. This has been motivated by the potential to create new microwave and antenna devices that exhibit superior characteristics compared to their conventional counterparts. A useful method for implementing planar metamaterials is based on reactively loaded transmission lines (TL). Such NRI-TE media consist of a network of printed transmission lines, periodically loaded with lumped-element series capacitors (Co) and shunt inductors (Lo) in a dual-TL (high-pass) configuration. The planar nature of the TL-based metamaterial (MTM) structures renders them well suited for the realization of planar microwave antennas and circuits. This paper discusses some antenna applications of NRI-TL metamaterials

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.013
GPT teacher head0.264
Teacher spread0.252 · 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 designSimulation or modeling
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

Citations4
Published2006
Admission routes1
Has abstractyes

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