{"id":"W1984869422","doi":"10.1016/s0959-1524(01)00047-6","title":"Real-time optimization under parametric uncertainty: a probability constrained approach","year":2002,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Process Optimization and Integration","field":"Engineering","cited_by":139,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robust optimization; Mathematical optimization; Stochastic programming; Parametric statistics; Sensitivity (control systems); Computer science; Nonlinear system; Uncertainty analysis; Nonlinear programming; Optimization problem; Stochastic optimization; Control theory (sociology); Mathematics; Engineering; Control (management); Artificial intelligence; Simulation","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":[0.004765929,0.001977798,0.003430906,0.001587259,0.000701789,0.003206045,0.002592502,0.002670029,0.00336243],"category_scores_gemma":[0.01440842,0.002202438,0.002334338,0.002174619,0.002518938,0.004834239,0.002716718,0.002372984,0.0003375664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001442957,"about_ca_system_score_gemma":0.001682531,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00509826,"about_ca_topic_score_gemma":0.00267039,"domain_scores_codex":[0.9978091,0.001078019,0.0001042113,0.0003328657,0.0004970258,0.0001787882],"domain_scores_gemma":[0.992706,0.00588356,0.0005512619,0.0002459869,0.0004520832,0.0001611489],"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":[0.0000238731,0.00002430524,0.00006859501,0.00006178892,0.00005895843,0.00004947636,0.00002421637,0.9595224,0.0002114466,0.03493144,0.0002459996,0.004777415],"study_design_scores_gemma":[0.000003111313,0.000006348876,0.00002257435,0.000003898846,0.000006916931,0.000004809493,0.000002525394,0.9905805,0.00004889746,0.009207455,0.0001082247,0.000004702013],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003937313,0.0005246641,0.992494,0.0003545313,0.00004535101,0.00002062738,0.00003090309,0.00005025231,0.002542323],"genre_scores_gemma":[0.7321438,0.00341428,0.2522211,0.0004756552,0.000590844,0.0004333536,0.0002420016,0.0004476762,0.01003134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00509826,"threshold_uncertainty_score":0.02520496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01360496043305783,"score_gpt":0.217147115594226,"score_spread":0.2035421551611681,"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."}}