{"id":"W2134082300","doi":"10.1109/acc.2012.6315339","title":"Matrix-wise approach for identification of multi-mode Switched ARX models with noise","year":2012,"lang":"en","type":"article","venue":"","topic":"Control Systems and Identification","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Kronecker product; Particle swarm optimization; Matrix (chemical analysis); Noise (video); Computer science; Nonlinear system; Iterative method; Mathematical optimization; Applied mathematics; Algorithm; Mathematics; Kronecker delta; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002431289,0.0001038774,0.0001643741,0.00007375808,0.00002815804,0.00002547081,0.0000885949,0.00005763023,0.000004220649],"category_scores_gemma":[0.000008281484,0.00008620317,0.00005215656,0.0000963678,0.00001006925,0.0004025424,0.000006194613,0.00003588037,0.000008005103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003492225,"about_ca_system_score_gemma":0.000006623127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006385014,"about_ca_topic_score_gemma":0.00001495816,"domain_scores_codex":[0.9992526,0.000009265032,0.000327788,0.0001194566,0.0001123455,0.0001786059],"domain_scores_gemma":[0.999474,0.00001694089,0.00007769866,0.0002789986,0.00009552087,0.00005686701],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004627298,0.0002201642,0.0007047985,0.0005759579,0.0001049831,3.011823e-8,0.001123212,0.3767355,0.6107457,0.007609006,0.0005912776,0.001543021],"study_design_scores_gemma":[0.0006120077,0.000006671218,0.001635829,0.000007405548,0.0000386089,0.000001110988,0.0001716043,0.9716628,0.02561577,0.0000380291,0.00009090305,0.0001193276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06199782,0.0002837798,0.9361715,0.00001256911,0.0001185869,0.000679589,0.00001794081,0.0001320424,0.0005861272],"genre_scores_gemma":[0.9803998,0.00000729165,0.0181604,0.000002230425,0.00007260422,0.0002526083,0.00004836083,0.00003026883,0.00102647],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.918402,"threshold_uncertainty_score":0.3515263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02338447297383747,"score_gpt":0.2466416178726434,"score_spread":0.223257144898806,"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."}}