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Record W2100280691 · doi:10.1109/lmwc.2002.801938

Simple and accurate technique for extracting the parasitic resistances of the dual-gate GaAs MESFET

2002· article· en· W2100280691 on OpenAlexaff
M. Ibrahim, B. Syrett, John R. Bennett

Bibliographic record

VenueIEEE Microwave and Wireless Components Letters · 2002
Typearticle
Languageen
FieldEngineering
TopicRadio Frequency Integrated Circuit Design
Canadian institutionsNortel (Canada)Carleton University
Fundersnot available
KeywordsMESFETMaterials scienceOptoelectronicsParasitic elementScalingGallium arsenideElectronic engineeringEquivalent circuitSimple (philosophy)Computer scienceVoltageElectrical engineeringField-effect transistorMathematicsEngineeringTransistor

Abstract

fetched live from OpenAlex

A procedure to extract the extrinsic resistances of the dual-gate GaAs MESFET (DGFET) is described. Six dc measurement setups are used to generate nine independent relations from which all the unknown extrinsic resistances of the DGFET are extracted. The described technique distinguishes between the forward bias and the nonforward bias values of the channel resistance. The extrinsic resistances of 29 devices with different topologies are determined using the developed technique. The extracted resistances follow normal scaling rules versus gate width. The developed procedure is a practical and accurate approach to extract the extrinsic resistances of the DGFET.

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 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 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 score0.009
Threshold uncertainty score0.582

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)0.0000.000

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 head0.026
GPT teacher head0.222
Teacher spread0.195 · 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 teacher head, 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

Citations0
Published2002
Admission routes1
Has abstractyes

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