MétaCan
Menu
Back to cohort
Record W2257532590

From component to circuit: advanced CAD tools for efficient RF/microwave integrated communication system design

2005· article· en· W2257532590 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Conference on Communications · 2005
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsToronto Metropolitan UniversityUniversity of Ottawa
Fundersnot available
KeywordsComponent (thermodynamics)Computer scienceCADMiniaturizationIntegrated circuitMicroelectronicsCircuit designElectronic engineeringPhysical designElectronic design automationComputer architectureProcess (computing)Computer Aided DesignIntegrated circuit designEmbedded systemEngineeringElectrical engineeringEngineering drawing
DOInot available

Abstract

fetched live from OpenAlex

As microelectronic technology continues to progress, there is an ever-increasing demand for higher levels of communication system integration and circuit miniaturization. This trend leads to massive and highly repetitive computational tasks during simulation, optimization and statistical analyses, requiring not only fast but also accurate computer aided design (CAD) tools so that the process can be achieved reliably. In this paper, the authors present a robust framework that combines the capabilities of neural networks and fuzzy systems to generate not only fast and accurate component models but also efficiently speed-up the circuit responses. The proposed approach is demonstrated through examples of device modeling and circuit design.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.952
Threshold uncertainty score1.000

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 science0.0030.000
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 head0.105
GPT teacher head0.304
Teacher spread0.199 · 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