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Record W2146806334 · doi:10.1109/simsym.2001.922141

Models of complex physical systems using Cell-DEVS

2002· article· en· W2146806334 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicCellular Automata and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsDEVSFormalism (music)Computer scienceDistributed computingComplex systemTheoretical computer scienceExtension (predicate logic)Modeling and simulationProgramming languageSimulationArtificial intelligence

Abstract

fetched live from OpenAlex

We present the definition of diverse models of physical systems using the Cell-DEVS paradigm. Cell-DEVS is an extension of the DEVS formalism that allows the definition of cellular models. We have developed a tool implementing these theoretical concepts, making easy the definition of cell spaces with explicit timing delays. Diversity of problems can be attacked in a simple fashion, reducing the development times of complex models. A wide variety of models have been developed using this approach, and here we include examples of a fire spreading model with different conditions, formation of a watershed and robots in a manufacturing plant. These examples allow us to show the potential application of the formalism and related tools to attack different problems.

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)0.000
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score0.195

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 head0.106
GPT teacher head0.259
Teacher spread0.153 · 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

Quick stats

Citations56
Published2002
Admission routes1
Has abstractyes

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