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Record W2058740198 · doi:10.1109/tap.2003.817556

Periodically loaded transmission line with effective negative refractive index and negative group velocity

2003· article· en· W2058740198 on OpenAlexaff
Omar Siddiqui, Mo Mojahedi, George V. Eleftheriades

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2003
Typearticle
Languageen
FieldMaterials Science
TopicMetamaterials and Metasurfaces Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGroup velocityTransmission lineRLC circuitResonatorCapacitorElectric power transmissionOpticsRefractive indexMetamaterialInductorGroup delay and phase delaySlow lightNegative refractionMaterials scienceScatteringCoplanar waveguideScattering parametersPhysicsElectrical engineeringTelecommunicationsVoltagePhotonic crystalComputer scienceEngineeringBandwidth (computing)

Abstract

fetched live from OpenAlex

We present the design and implementation of a periodically loaded transmission line, which simultaneously exhibits negative refractive index (NRI) and negative group delay (and, hence, negative group velocity). This is achieved by loading the transmission line in series with capacitors and RLC resonators and in shunt with inductors. We discuss the dispersion characteristics of such a medium and identify the frequency bands of NRI and negative group delay. The structures are theoretically studied using S-parameters simulations on truncated loaded transmission lines of different lengths, and the predicted results are compared to the measured scattering parameters of such lines printed on circuit boards using coplanar waveguide technology.

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.012
GPT teacher head0.241
Teacher spread0.229 · 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

Citations282
Published2003
Admission routes1
Has abstractyes

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