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Record W2159981061 · doi:10.1109/bipol.1992.274049

An accurate quasi-static method for determining the excess phase shift in the base region of bipolar transistors

2003· article· en· W2159981061 on OpenAlexaff
J.S. Hamel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsBipolar junction transistorTransistorCommon emitterComputer scienceElectronic circuitBase (topology)Electronic engineeringComputational physicsPhase (matter)PhysicsElectrical engineeringVoltageOptoelectronicsEngineeringMathematicsQuantum mechanics

Abstract

fetched live from OpenAlex

The conventional quasi-static approach has been extended to enable the accurate calculation of the phase shift of the common emitter current gain up to the transition frequency solely from static charge distributions for bipolar transistors with arbitrary base impurity profiles. Accurate knowledge of the phase shift allows the use of simple, yet accurate, high-frequency compact bipolar transistor models which use this information to determine critical model parameters. The accuracy of this approach was assessed by AC numerical simulation. The ability of the approach to estimate the phase shift of the common emitter current gain from static charge distributions allows accurate predictive high-frequency AC modeling of both digital and analog bipolar and BiCMOS circuits without the need for high-frequency, time-dependent device simulation or high-frequency device measurements.>

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.009

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 science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.062
GPT teacher head0.344
Teacher spread0.282 · 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 designSimulation or modeling
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

Citations11
Published2003
Admission routes1
Has abstractyes

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