MétaCan
Menu
Back to cohort
Record W2156830051 · doi:10.1109/icsmc.1997.635199

GPNSAT: A new tool for simulation and analysis of hybrid systems

2002· article· en· W2156830051 on OpenAlexaff
Mahmoud Rezai, M.R. Ito, P.D. Lawrence

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicPetri Nets in System Modeling
Canadian institutionsUniversity of British ColumbiaUniversity of Waterloo
Fundersnot available
KeywordsPetri netReachabilityComputer scienceHybrid systemSimple (philosophy)Tree (set theory)Process architectureDistributed computingStochastic Petri netSoftware engineeringSystems engineeringTheoretical computer scienceProgramming languageMachine learningEngineeringMathematics

Abstract

fetched live from OpenAlex

Some of the main issues in development and use of a tool for simulation and analysis of hybrid systems are discussed. This tool called GPNSAT (global Petri net simulation and analysis tool) was developed to assist in our research into hybrid systems. GPNSAT simulates simple, timed and and global Petri nets. The analysis of nets is performed by both reachability tree and algebraic methods. The main advantages of the tool are its ease of use, simple implementation and its ability to model hybrid systems.

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 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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.918
Threshold uncertainty score0.233

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.055
GPT teacher head0.281
Teacher spread0.226 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2002
Admission routes1
Has abstractyes

Explore more

Same topicPetri Nets in System ModelingFrench-language works237,207