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Record W1969653489 · doi:10.1109/apmc.2007.4554743

Application of EM Coupling CAD Model to Nonlinear Integrated Circuit Simulation

2007· article· en· W1969653489 on OpenAlexaff
Navid Arbabi, Vijay Devabhaktuni, M.C.E. Yagoub

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of OttawaConcordia University
Fundersnot available
KeywordsElectronic engineeringCADCoupling (piping)Equivalent circuitCircuit extractionDiscrete circuitNonlinear systemComputer scienceIntegrated circuitElectronic circuitCircuit designMicrowaveElectronic circuit simulationElectrical engineeringEngineeringPhysicsTelecommunicationsEngineering drawing

Abstract

fetched live from OpenAlex

Modern RF/microwave integrated circuits are getting denser and/or compact in terms of number of circuit elements per unit area thereby leading to increased parasitic EM coupling. An efficient and recent CAD model for EM coupling based on circuit theory and deembedding concepts previously applied to passive EM circuit simulation is considered. For the first time, this new CAD technique is applied to EM coupling modeling of a nonlinear RF integrated circuit consisting of both active and passive components. The resulting circuit-level model is shown to be efficient for circuit simulation in terms of CPU-time.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.013

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 communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.017
GPT teacher head0.247
Teacher spread0.230 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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