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Record W1984593609 · doi:10.1116/1.582174

Direct extraction of the channel thermal noise in metal-oxide-semiconductor field effect transistor from measurements of their rf noise parameters

2000· article· en· W1984593609 on OpenAlex
Chih‐Hung Chen, M. Jamal Deen

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Vacuum Science & Technology A Vacuum Surfaces and Films · 2000
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNoise (video)Materials scienceTransconductanceMOSFETField-effect transistorNoise generatorTransistorFlicker noiseOptoelectronicsY-factorNoise figureNoise temperatureExtraction (chemistry)Electronic engineeringElectrical engineeringEngineeringCMOSPhase noiseChemistryComputer scienceAmplifier

Abstract

fetched live from OpenAlex

This article presents an extraction method to obtain the channel thermal noise in metal-oxide-semiconductor field effect transistor (MOSFETs) directly from the dc, scattering parameter and rf noise measurements. In this extraction method, the transconductance (gm), output resistance (RDS), and source and drain resistances (RS and RD) are obtained from dc measurements. The gate resistance (RG) is extracted from scattering-parameter measurements, and the equivalent noise resistance (Rn) is obtained from rf noise measurements. This method has been verified by using the measured data of a 0.36 μm n-type MOSFET up to 18 GHz. Comparisons between simulated and measured characteristics of noise parameters versus frequency are also presented.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.222
Teacher spread0.206 · 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