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Record W4237537986 · doi:10.1109/wsc.2018.8632408

INTRODUCTION TO THE DISCRETE EVENT SYSTEM SPECIFICATION FORMALISM AND ITS APPLICATION FOR MODELING AND SIMULATING CYBER-PHYSICAL SYSTEMS

2018· article· en· W4237537986 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

Venue2018 Winter Simulation Conference (WSC) · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicSimulation Techniques and Applications
Canadian institutionsCarleton University
Fundersnot available
KeywordsDEVSFormalism (music)Computer scienceModular designDiscrete event simulationExploitTheoretical computer scienceFormal specificationModeling and simulationProgramming languageDistributed computingSoftware engineeringSimulationComputer security

Abstract

fetched live from OpenAlex

The Discrete Event System Specification (DEVS) formalism is a set of conventions for specifying discrete event simulation models. In this tutorial, we introduce the core concepts of DEVS. First, we introduce a set of informal requirements from which a formal specification is to be developed. Then, we present different modeling conventions at different levels of abstraction. The tutorial exploits the DEVS formalism's support for modular model design. The concepts are discussed with an example of cyber-physical systems modeling and implementation, which can be used to understand the main concepts of the formalism.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.815
Threshold uncertainty score0.647

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.115
GPT teacher head0.398
Teacher spread0.283 · 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