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Record W2063941955 · doi:10.1002/mop.25951

Efficient characterization of multilayered microwave wireless circuits on gyrotropic dielectric media including magnetized ferrites

2011· article· en· W2063941955 on OpenAlexaff
Mohamed Lamine Tounsi, M.C.E. Yagoub

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAnisotropyFerrite (magnet)MicrowaveWirelessCharacterization (materials science)Materials scienceRadio frequencyElectronic circuitElectronic engineeringDispersion (optics)DielectricElectrical engineeringOptoelectronicsEngineeringTelecommunicationsPhysicsOpticsNanotechnology

Abstract

fetched live from OpenAlex

Abstract The ever‐growing use of anisotropic ferrite devices in modern wireless communication systems highlighted the need for robust design tools to reliably characterize the dispersion behavior of such devices in radio frequency (RF)/microwave bands, especially for multilayered configurations. Indeed, as ferrites present a biaxial anisotropy, spectral analysis of multilayered configurations with such substrates is not generalized, however, restricted to some particular cases of tensors. Therefore, this article deals with the characterization of anisotropy effects on the dispersion parameters of multilayered wireless circuits with ferrite substrates, particular case of gyrotropic medias. In the proposed approach, a rigorous analysis was carried out by taking into account, for the first time, the electrical aspect of anisotropy. The computed results are in good agreement with those available in the literature. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:978–982, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.25951

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 score0.043
Threshold uncertainty score0.971

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 head0.022
GPT teacher head0.210
Teacher spread0.188 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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