{"id":"W4399340559","doi":"10.1109/lcsys.2024.3409456","title":"Risk-Aware Finite-Horizon Social Optimal Control of Mean-Field Coupled Linear-Quadratic Subsystems","year":2024,"lang":"en","type":"article","venue":"IEEE Control Systems Letters","topic":"Aquatic and Environmental Studies","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Horizon; Quadratic equation; Control (management); Field (mathematics); Mathematics; Control theory (sociology); Computer science; Mathematical optimization; Applied mathematics; Pure mathematics; 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":[0.002072666,0.001118126,0.001455475,0.0004185921,0.0004536486,0.00155787,0.001268727,0.001478241,0.002303358],"category_scores_gemma":[0.00434732,0.0005961577,0.0008005137,0.0003839387,0.001796974,0.001087425,0.002097274,0.001362159,0.0002137294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001515613,"about_ca_system_score_gemma":0.001750408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01045347,"about_ca_topic_score_gemma":0.005207323,"domain_scores_codex":[0.9991542,0.0003010963,0.00002449714,0.0001818806,0.000176294,0.0001620355],"domain_scores_gemma":[0.9975159,0.001568393,0.0003581298,0.00009158888,0.0003213802,0.0001444828],"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":[0.00003283836,0.00001248753,0.0001396442,0.00002779762,0.00002429848,0.00003197186,0.0000320959,0.9862579,0.0005101553,0.01093066,0.000249846,0.001750238],"study_design_scores_gemma":[0.000006809472,0.00001624646,0.0000566597,0.000003159516,0.000004863429,0.000003169962,0.000008707172,0.9947931,0.00008588926,0.00491721,0.0001000045,0.000004176241],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04469566,0.0002149092,0.9483321,0.0006460111,0.00005885856,0.00004381177,0.00009308528,0.000135871,0.005779734],"genre_scores_gemma":[0.9779888,0.0001188867,0.01717243,0.0001153151,0.0000376835,0.0001194608,0.00005529932,0.00004038568,0.004351803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01045347,"threshold_uncertainty_score":0.02078521,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009782920999534603,"score_gpt":0.1995211612227974,"score_spread":0.1897382402232629,"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."}}