{"id":"W3075387873","doi":"10.1016/j.compchemeng.2020.107055","title":"Mixed H/Passivity controller design through LMI approach applicable for waterflooding optimization in the presence of geological uncertainty","year":2020,"lang":"en","type":"article","venue":"Computers & Chemical Engineering","topic":"Reservoir Engineering and Simulation Methods","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Passivity; Controller (irrigation); Control theory (sociology); Computer science; Mathematics; Control engineering; Engineering; Control (management); Biology; 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":[0.0005308419,0.0009927682,0.000858242,0.0002905642,0.0004161274,0.001242171,0.0006489417,0.000922015,0.004995345],"category_scores_gemma":[0.0007891561,0.0004053313,0.0005773506,0.0002921422,0.0005016857,0.000670051,0.0007484611,0.001019995,0.0006881193],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004019342,"about_ca_system_score_gemma":0.000892949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003178282,"about_ca_topic_score_gemma":0.003179086,"domain_scores_codex":[0.9997514,0.00006181307,0.00001517852,0.00006168447,0.0000804247,0.00002957114],"domain_scores_gemma":[0.9997084,0.0001264851,0.00003853035,0.00001825798,0.00009978869,0.000008655198],"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":[0.0001730846,0.00007454294,0.0003002021,0.0005781908,0.0001197394,0.0001823955,0.0001906169,0.8632714,0.02099256,0.0210455,0.002641107,0.09043059],"study_design_scores_gemma":[0.00001990003,0.0001133946,0.0001287883,0.0000170616,0.00001806408,0.00001931914,0.00001694348,0.9922858,0.002716753,0.002996065,0.001656767,0.00001107912],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005609666,0.0001889232,0.987114,0.0001107381,0.00005943819,0.00004267366,0.00005347787,0.0002603959,0.006560728],"genre_scores_gemma":[0.8671553,0.000491038,0.1190196,0.0002668233,0.0001001784,0.0004802238,0.0002345901,0.0001361869,0.01211609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004995345,"threshold_uncertainty_score":0.01671112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05225580607892669,"score_gpt":0.2407553348371005,"score_spread":0.1884995287581738,"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."}}