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Record W4255714343 · doi:10.1109/mwscas.2000.951607

Limitations of criteria for testing transistor circuits for multiple DC operating points

2002· article· en· W4255714343 on OpenAlexaff
L. Kronenberg, W. Mathis, L. Trajkovic

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNumerical Methods and Algorithms
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsResistorTransistorJacobian matrix and determinantElectronic circuitEquivalent circuitComputer scienceControl theory (sociology)Value (mathematics)Topology (electrical circuits)MathematicsElectronic engineeringElectrical engineeringEngineeringStatisticsVoltageControl (management)Applied mathematics

Abstract

fetched live from OpenAlex

Addresses the problem of determining whether a transistor circuit possesses multiple dc operating points. We investigate how the sign change of the determinant corresponding to the Jacobian matrix associated with circuit equations can be used to indicate the number of dc operating points in a transistor circuit. We give circuit examples that illustrate that these criteria may not be reliable, and show that resistor values that determine the number of a circuit's dc operating points, may or may not affect the value of the calculated determinant. Even if the mere existence of a feedback structure depends on whether a particular resistor is open- or short-circuited, the resistor value may not affect the value of the determinant. Hence, the determinant criteria is not always indicative of the number of a circuit's dc operating points.

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)0.018
metaresearch head score (Gemma)0.175
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: Methods · Consensus signal: Methods
Teacher disagreement score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.175
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.002
Science and technology studies0.0010.004
Scholarly communication0.0030.004
Open science0.0030.003
Research integrity0.0020.002
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 head0.313
GPT teacher head0.339
Teacher spread0.026 · 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
GenreMethods

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

Citations1
Published2002
Admission routes1
Has abstractyes

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