{"id":"W2491486735","doi":"10.4018/978-1-4666-4034-4.ch001","title":"Nonblocking Supervisory Control of Flexible Manufacturing Systems Based on State Tree Structures","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in civil and industrial engineering book series","topic":"Petri Nets in System Modeling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Supervisory control; Petri net; Event (particle physics); Tree (set theory); Variety (cybernetics); Computer science; Representation (politics); State (computer science); Benchmark (surveying); Control (management); Distributed computing; Control logic; Supervisory control theory; Control engineering; Engineering; Mathematics; Programming language; Artificial intelligence","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":[0.000128376,0.0003420173,0.0002248782,0.0001773955,0.0001784856,0.0006077561,0.0004166585,0.0001843323,0.002402013],"category_scores_gemma":[0.0002363687,0.0001424279,0.0002489893,0.0002758795,0.0003622031,0.0006026378,0.0002872178,0.0005030351,0.0002522485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000404125,"about_ca_system_score_gemma":0.0004430856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007344658,"about_ca_topic_score_gemma":0.00104682,"domain_scores_codex":[0.999899,0.00001375189,0.00000511497,0.00002233123,0.00004943065,0.00001032393],"domain_scores_gemma":[0.9999121,0.00004481813,0.00001204418,0.000008951274,0.00001746824,0.000004522497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00011953,0.00007158883,0.0002480566,0.0003651301,0.00002629711,0.0002156314,0.0003719201,0.2822511,0.09586201,0.3131449,0.004260983,0.3030629],"study_design_scores_gemma":[0.00002216647,0.0001546962,0.0005330468,0.00007226871,0.00001993895,0.0001125042,0.00004649335,0.8429915,0.02539672,0.09534498,0.03528645,0.00001927315],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03010178,0.00206314,0.9232656,0.0002249844,0.0001705123,0.00004890658,0.00007457846,0.0008312654,0.04321906],"genre_scores_gemma":[0.806333,0.004733627,0.1548185,0.0001340819,0.0001274951,0.0001540366,0.000269533,0.0001342541,0.03329553],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002402013,"threshold_uncertainty_score":0.008035541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02235174409023688,"score_gpt":0.2040796536694317,"score_spread":0.1817279095791948,"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."}}