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Record W2018465987 · doi:10.1109/mmm.2011.2173869

Device and IC Characterization Above 100 GHz

2012· article· en· W2018465987 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

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.

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 categoriesInsufficient payload (model declined to judge)
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 score0.061
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.218
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