{"id":"W2161197940","doi":"10.1002/aic.12112","title":"Robust identification of piecewise/switching autoregressive exogenous process","year":2009,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Control Systems and Identification","field":"Engineering","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Outlier; Expectation–maximization algorithm; Autoregressive model; Algorithm; Mathematical optimization; Computer science; Maximization; Identification (biology); Mathematics; Artificial intelligence; Maximum likelihood","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001049467,0.0004966285,0.0006899245,0.0004268005,0.0001657065,0.000564963,0.0007522513,0.0004066812,0.0009623895],"category_scores_gemma":[0.0026467,0.0002524858,0.0005879335,0.0004783556,0.000369023,0.0005223505,0.0005770241,0.0008068894,0.000217351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003050001,"about_ca_system_score_gemma":0.0003354276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001588604,"about_ca_topic_score_gemma":0.0006645641,"domain_scores_codex":[0.9994991,0.0001538228,0.00002051937,0.0001288242,0.0001492491,0.00004852104],"domain_scores_gemma":[0.9991958,0.0004290502,0.0001786866,0.00007768085,0.0001040385,0.00001484835],"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":[0.0001286015,0.0000294827,0.0009598461,0.00008474971,0.0000628764,0.0001085782,0.0000590191,0.9112145,0.01275704,0.01161604,0.0003660615,0.06261315],"study_design_scores_gemma":[0.000002172497,0.00001580746,0.0003256801,0.000001814339,0.000004005872,0.00001379515,0.000004028099,0.9969704,0.001328105,0.001114604,0.0002160882,0.00000348567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02736544,0.00008249429,0.9715071,0.00003492982,0.00001186015,0.00001532791,0.00004039629,0.0002666257,0.0006759037],"genre_scores_gemma":[0.8859364,0.0001495952,0.1119254,0.00002498193,0.00001965368,0.00006182714,0.0001879251,0.0000462286,0.001647903],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001588604,"threshold_uncertainty_score":0.005550206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01163359998158322,"score_gpt":0.2201232247965853,"score_spread":0.2084896248150021,"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."}}