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Record W2018465987 · doi:10.1109/mmm.2011.2173869

Device and IC Characterization Above 100 GHz

2012· article· en· W2018465987 on OpenAlexaff
Kenneth H. K. Yau, Eric Dacquay, Ioannis Sarkas, Sorin P. Voinigescu

Bibliographic record

VenueIEEE Microwave Magazine · 2012
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceCharacterization (materials science)TransistorOptoelectronicsSilicon-germaniumBipolar junction transistorHeterojunction bipolar transistorElectronic circuitField-effect transistorSiliconHeterojunctionSemiconductor deviceScalingElectrical engineeringSemiconductorElectronic engineeringGermaniumEngineeringVoltageNanotechnology

Abstract

fetched live from OpenAlex

Due to the aggressive scaling of metal-oxide-semiconductor field-effect transistors (MOSFETs) and silicon germanium SiGe heterojunction bipolar transistors (HBTs), silicon-based circuits operating above 100 GHz are becoming a reality. However, at present, most, if not all semiconductor foundries extract their transistor and passive device models from measurements conducted below 110 GHz and often below 65 GHz. In order to reduce the number of design iterations, accurate S-parameter characterization techniques above 100 GHz are required for active and passive devices such that compact models may be developed and verified on representative circuits.

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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.218
Teacher spread0.200 · 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

Citations46
Published2012
Admission routes1
Has abstractyes

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