{"id":"W4285012347","doi":"10.22215/etd/2022-15065","title":"Supervisory Control Using DEVS with Approximate Method &amp; Hybrid Layer","year":2022,"lang":"en","type":"dissertation","venue":"","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Supervisory control; DEVS; Supervisory control theory; Formalism (music); Computer science; State space; Control engineering; Controller (irrigation); Control (management); Modeling and simulation; Distributed computing; Artificial intelligence; Engineering; Simulation; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001109007,0.0004462524,0.0005294666,0.0003832496,0.0003663167,0.001163783,0.001217082,0.0005365126,0.003169999],"category_scores_gemma":[0.002346054,0.0003895757,0.0007223464,0.0003160591,0.000780688,0.001162665,0.001330799,0.0009952385,0.0003833057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006857073,"about_ca_system_score_gemma":0.001145491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002695138,"about_ca_topic_score_gemma":0.002051371,"domain_scores_codex":[0.9990875,0.0001840407,0.00007036929,0.0001377786,0.0004617341,0.00005857221],"domain_scores_gemma":[0.9988179,0.0005375303,0.00009907613,0.0003162376,0.0001925942,0.00003658053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001578021,0.00005443395,0.001022415,0.0003481376,0.00007732973,0.0001864165,0.0003014725,0.6958572,0.02269134,0.1491881,0.001403956,0.1287113],"study_design_scores_gemma":[0.00001734807,0.00003020307,0.00007690957,0.00001753714,0.00001052908,0.00004081548,0.00001237137,0.9748521,0.006600271,0.01173535,0.00659776,0.000008837101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004641381,0.00005914028,0.9925978,0.00003457134,0.0000168652,0.00002883691,0.00003615966,0.0008412141,0.001743998],"genre_scores_gemma":[0.4080164,0.0001823432,0.5874726,0.00006202591,0.00001848307,0.0002755389,0.0002246162,0.0002105453,0.003537413],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003169999,"threshold_uncertainty_score":0.01060474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06370905253868173,"score_gpt":0.3184327458767425,"score_spread":0.2547236933380608,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}