{"id":"W1756823618","doi":"10.1109/vims.2001.924897","title":"Intelligent monitoring system used to control asynchronous production systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Elevator Systems and Control","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Production (economics); Asynchronous communication; Computer science; Control (management); Production control; Supervisory control; Production manager; Production system (computer science); Systems engineering; Risk analysis (engineering); Real-time computing; Engineering; Telecommunications; Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001802753,0.0001946032,0.0003053191,0.0001045142,0.00007224535,0.0000920465,0.0001290205,0.00007706142,0.00002197115],"category_scores_gemma":[0.00001466733,0.0001752218,0.00005992326,0.0001719592,0.000005862013,0.0001068493,0.000008531766,0.0001016692,0.0007488129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003502198,"about_ca_system_score_gemma":0.000004032235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001787435,"about_ca_topic_score_gemma":0.00001558772,"domain_scores_codex":[0.9987862,0.00003400249,0.000384091,0.0002321491,0.0002287184,0.0003348022],"domain_scores_gemma":[0.9993734,0.00002457458,0.00003129219,0.0003478969,0.00006789174,0.0001549379],"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":[0.0000216994,0.0001060918,0.00925118,0.002105385,0.0006920871,0.00005621089,0.003953747,0.8452458,0.09865469,0.005205878,0.00760198,0.02710524],"study_design_scores_gemma":[0.001691448,0.0002831642,0.001098925,0.001339833,0.0001323433,0.0002090787,0.00742105,0.9135064,0.04407314,0.000002131831,0.0288139,0.001428532],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.793293,0.006912066,0.1677956,0.0001387985,0.01631693,0.002523107,0.000007530881,0.003426854,0.009586093],"genre_scores_gemma":[0.9971939,0.000008438192,0.0000577487,0.000004335355,0.001401913,0.0002772394,3.316531e-7,0.00004881362,0.001007298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2039009,"threshold_uncertainty_score":0.9624724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01732037577620275,"score_gpt":0.1974844771994894,"score_spread":0.1801641014232866,"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."}}