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Record W2120640238 · doi:10.1109/tpwrs.2003.821620

Order Reduction of the Dynamic Model of a Linear Weakly Periodic System–Part I: General Methodology

2004· article· en· W2120640238 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 Transactions on Power Systems · 2004
Typearticle
Languageen
FieldDecision Sciences
TopicProbabilistic and Robust Engineering Design
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLTI system theoryLinearizationReduction (mathematics)Control theory (sociology)MathematicsLinear systemModel order reductionConvergence (economics)Singular value decompositionApplied mathematicsGauss–Seidel methodGaussElectric power systemComputer scienceMathematical optimizationNonlinear systemAlgorithmMathematical analysisIterative methodPower (physics)PhysicsControl (management)

Abstract

fetched live from OpenAlex

A methodology is presented for the order reduction of the dynamic model of a linear weakly periodic system obtained by linearization about the nonsinusoidal periodic steady state. It consists of two stages. First, the time-invariant part of the original full-order system is approximated by a reduced system by using singular value decomposition techniques. Then the time-varying part of the reduced system is calculated by using a Gauss-Seidel technique. The issues of sparsity, convergence, and accuracy are analyzed. The example used for illustration serves to demonstrate the efficiency of the new method.

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)0.002
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.487

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.101
GPT teacher head0.326
Teacher spread0.225 · 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