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Record W2019158573 · doi:10.1002/mop.26658

Group delay swing enhancement in transmission‐line all‐pass networks using coupling and dispersion boosting ferrimagnetic substrate

2012· article· en· W2019158573 on OpenAlexaff
Shulabh Gupta, Louis‐Philippe Carignan, Christophe Caloz

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2012
Typearticle
Languageen
FieldEngineering
TopicPhotonic and Optical Devices
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsSwingBoosting (machine learning)MicrowaveFerrimagnetismMaterials scienceDispersion (optics)Group delay and phase delayFerrite (magnet)Coupling (piping)Transmission lineElectronic engineeringOptoelectronicsElectrical engineeringComputer scienceEngineeringTelecommunicationsPhysicsMagnetic fieldAcousticsOpticsFilter (signal processing)

Abstract

fetched live from OpenAlex

Abstract The principle of group delay swing enhancement in a transmission‐line all‐pass network using the combined coupling and dispersion boosting properties of a ferromagnetic substrate is proposed; full‐wave verified and experimentally demonstrated using ferrite substrates as a proof of concept. The proposed group delay swing enhanced structures are compact in size, exhibiting a larger dispersion per unit area compared with other alternative techniques for dispersion enhancement, and a magnetically tunable group delay swing. The proposal to suppress the requirement of an external magnet is discussed based on self‐biased ferromagnetic nanowire substrates and expected improvements are further pointed out. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:589–593, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26658

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.835

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 head0.012
GPT teacher head0.221
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 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

Citations4
Published2012
Admission routes1
Has abstractyes

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