{"id":"W1991700945","doi":"10.1109/tcst.2006.883240","title":"Multirate Minimum Variance Control Design and Control Performance Assessment: A Data-Driven Subspace Approach","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Control Systems Technology","topic":"Control Systems and Identification","field":"Engineering","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Benchmark (surveying); Subspace topology; Control theory (sociology); Controller (irrigation); Computer science; Variance (accounting); Transfer function; Set (abstract data type); Minimum-variance unbiased estimator; Mathematical optimization; Algorithm; Mathematics; Engineering; Control (management); Artificial intelligence; Statistics; Mean squared error","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":[0.001659852,0.0004910115,0.0009115508,0.0006914743,0.0003370428,0.0001573653,0.0006341667,0.0005779617,0.000005766418],"category_scores_gemma":[0.00001768383,0.0004888946,0.00008543541,0.0004553545,0.0001610699,0.0004818517,0.000003079037,0.0006894052,0.00004251294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000225258,"about_ca_system_score_gemma":0.000058939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007449889,"about_ca_topic_score_gemma":0.00009026754,"domain_scores_codex":[0.9969475,0.0001935732,0.0009492786,0.0007974085,0.0003381345,0.0007741573],"domain_scores_gemma":[0.9976268,0.0004466531,0.0002438541,0.001323099,0.0001898702,0.0001696537],"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":[0.0005065017,0.000305496,0.0004829376,0.0004535863,0.001233819,0.00002773819,0.0001256556,0.8321941,0.1412645,0.0005520543,0.0002563364,0.02259725],"study_design_scores_gemma":[0.008323934,0.0002035197,0.0005863276,0.00008976361,0.0002567329,0.0001163032,0.000151031,0.9875624,0.0006561379,0.000008402956,0.001588324,0.0004571282],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01391709,0.00111321,0.9786956,0.0002366528,0.001460642,0.002942623,0.0002052492,0.00119577,0.0002331494],"genre_scores_gemma":[0.9968544,0.0001070597,0.001785682,0.00004019342,0.0001422326,0.0007285967,0.000009413926,0.00009025724,0.0002422063],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9829373,"threshold_uncertainty_score":0.9997563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01716351600617633,"score_gpt":0.2330999850428427,"score_spread":0.2159364690366664,"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."}}