MétaCan
Menu
Back to cohort
Record W2096967253 · doi:10.1002/mmce.20896

Effect of stepped-impedance resonators on rectangular metamaterial unit cells

2015· article· en· W2096967253 on OpenAlexaff
Behnam Zarghooni, Abdolmehdi Dadgarpour, Tayeb A. Denidni

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsMiniaturizationMetamaterialResonatorElectrical impedanceSpiral (railway)Materials scienceMicrowaveUnit (ring theory)Resonance (particle physics)OptoelectronicsAcousticsElectrical engineeringElectronic engineeringPhysicsEngineeringMathematicsTelecommunicationsNanotechnologyMechanical engineering

Abstract

fetched live from OpenAlex

In this article, effect of the stepped-impedance resonator (SIR) miniaturization technique on rectangular metamaterial unit cells is investigated and the influence of the method's structural parameters on the characteristic impedance and the distance between higher resonance modes is discussed. According to the results, the ideal unit cell for this method should be thick enough and have an impedance ratio greater than one. Furthermore, the SIR technique is applied on a conventional two-turn spiral metamaterial unit cell and a new compact spiral unit cell is introduced. The effect of this method on the unit cell parameters is investigated and the new unit cell is compared to the conventional spiral. According to the results, a miniaturization factor of 0.75 can be achieved with the new unit cell. To validate the results, a two dimensional array of the unit cell is fabricated and its S-parameters are measured using the free space method. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:582–590, 2015.

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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
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)0.0010.000

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 head0.008
GPT teacher head0.218
Teacher spread0.209 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of RF and Microwave Computer-Aided EngineeringSame topicAntenna Design and AnalysisFrench-language works237,207