{"id":"W4214528141","doi":"10.1002/aic.17665","title":"A nested online scheduling and nonlinear model predictive control framework for multi‐product continuous systems","year":2022,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Model predictive control; Scheduling (production processes); Nested loop join; Computer science; Nonlinear system; Mathematical optimization; Control theory (sociology); Dynamic priority scheduling; Control (management); Mathematics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001148294,0.0007079486,0.0007142043,0.00026531,0.0003245476,0.0007366601,0.001043069,0.0007092164,0.0017541],"category_scores_gemma":[0.0009878625,0.0003805912,0.0005341995,0.000244588,0.000956786,0.0007686093,0.0007807438,0.001165538,0.0001648056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001063294,"about_ca_system_score_gemma":0.001519662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0108123,"about_ca_topic_score_gemma":0.006406813,"domain_scores_codex":[0.9995342,0.000171087,0.00001465613,0.00006639842,0.0001706844,0.00004305803],"domain_scores_gemma":[0.9995977,0.0001857473,0.00005858861,0.00003535329,0.00009353793,0.00002905014],"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":[0.00001477879,0.0000217663,0.0000550399,0.00001777338,0.000005441514,0.00002699193,0.00002009128,0.988379,0.0008846342,0.007067944,0.00008351512,0.003423086],"study_design_scores_gemma":[0.000001728425,0.000006715965,0.000009779765,6.839546e-7,6.216981e-7,9.774678e-7,9.928777e-7,0.9990947,0.0000691976,0.000744072,0.0000697467,7.451162e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0154586,0.0001934477,0.9808428,0.000129705,0.00003468871,0.00003432237,0.00002396144,0.0001384976,0.003143946],"genre_scores_gemma":[0.9094045,0.0001602292,0.08786987,0.00004890556,0.00004730809,0.0001055575,0.00003967206,0.00003478868,0.002289152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0108123,"threshold_uncertainty_score":0.02149874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01627866575876871,"score_gpt":0.2550573363424345,"score_spread":0.2387786705836658,"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."}}