{"id":"W3210007706","doi":"10.1007/978-3-030-81843-2_19","title":"The Inconsistent Linear Quadratic Regulator","year":2021,"lang":"en","type":"book-chapter","venue":"Springer finance","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Control theory (sociology); Linear-quadratic regulator; Regulator; Quadratic equation; State (computer science); Point (geometry); Control (management); Simple (philosophy); Mathematics; Term (time); Computer science; Optimal control; Mathematical optimization; Physics; Algorithm; Geometry; Artificial intelligence; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009856207,0.0003157406,0.0003611249,0.00003923552,0.0001305363,0.0000492572,0.0002178077,0.0002211794,0.00001953865],"category_scores_gemma":[0.000036933,0.0002796421,0.0001372497,0.00003754808,0.00005589829,0.00006910981,0.00005948486,0.0003475788,0.0001429894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001764553,"about_ca_system_score_gemma":0.0000489425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001808595,"about_ca_topic_score_gemma":0.00003632219,"domain_scores_codex":[0.9988205,0.000008892324,0.0004261623,0.0002849831,0.0002088083,0.0002506942],"domain_scores_gemma":[0.9988829,0.00007859869,0.0001375638,0.0007591042,0.000105186,0.00003658814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001556543,0.000007277704,0.00001715427,0.0004292753,0.0003087118,0.00009890866,0.00008304455,0.446633,0.0002517381,0.5101743,0.002228596,0.03975246],"study_design_scores_gemma":[0.0001961593,0.00001172359,0.00005526322,0.0005176424,0.00004022454,0.000008395169,0.000003683752,0.04333504,0.0001050261,0.001729661,0.9535379,0.0004592493],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0002775211,0.125023,0.06819049,0.000471273,0.005994911,0.001513536,0.00004816612,0.001143354,0.7973377],"genre_scores_gemma":[0.01798112,0.007739242,0.006518204,0.00005698777,0.0009446635,0.0001186077,0.00002612837,0.0003223604,0.9662927],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9513093,"threshold_uncertainty_score":0.9999655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007229582690630675,"score_gpt":0.184248916096649,"score_spread":0.1770193334060183,"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."}}