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Record W2118163517 · doi:10.1177/0037549712450360

System theoretic foundations of modeling and simulation: a historic perspective and the legacy of A Wayne Wymore

2012· article· en· W2118163517 on OpenAlexaff
Tuncer Ören, Bernard P. Zeigler

Bibliographic record

VenueSIMULATION · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsRelation (database)Computer sciencePerspective (graphical)Modeling and simulationSoftware engineeringDiscrete event simulationEvent (particle physics)Systems engineeringTheoretical computer scienceArtificial intelligenceEngineeringSimulationData mining

Abstract

fetched live from OpenAlex

AW Wymore, the founder of the world’s first systems engineering department at the University of Arizona, has been at the origin of the system theoretic foundations of modeling and simulation. Wymore’s intellectual family tree, which goes back to Gauss and Weierstrass, is given. How the authors met, cooperated, and advocated system theory for the advancement of modeling and simulation are explained. The concept of model-based simulation was also one of the outcomes of this cooperation. This article reviews the emergence of systems-theory-based modeling and simulation languages and environments, such as the General System Theory implementor and Discrete Event System Specification, and their relation to Wymore’s concepts. We also discuss the application of powerful software development frameworks to support user-friendly access to systems concepts and to increase the power to support systems design and engineering.

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)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.998
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0020.022
Scholarly communication0.0050.014
Open science0.0010.002
Research integrity0.0020.010
Insufficient payload (model declined to judge)0.0020.001

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 head0.098
GPT teacher head0.412
Teacher spread0.314 · 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.

Study designNot applicable
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

Citations42
Published2012
Admission routes1
Has abstractyes

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