{"id":"W4389831853","doi":"10.1002/aic.18326","title":"Data‐driven parallel Koopman subsystem modeling and distributed moving horizon state estimation for large‐scale nonlinear processes","year":2023,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Nanyang Technological University","keywords":"Nonlinear system; Process state; Estimator; Process (computing); Computer science; State (computer science); Scale (ratio); Mathematical optimization; Process modeling; Control theory (sociology); Algorithm; Mathematics; Work in process; Artificial intelligence; Engineering","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":[0.001087023,0.0008780743,0.0008684827,0.0003777236,0.0004338213,0.000681814,0.001059235,0.0007879156,0.0009920576],"category_scores_gemma":[0.0024154,0.0004937165,0.0006392146,0.0004689633,0.001053184,0.001213191,0.0009889464,0.001304554,0.0001341244],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000926575,"about_ca_system_score_gemma":0.001398272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01128682,"about_ca_topic_score_gemma":0.008251208,"domain_scores_codex":[0.9995684,0.0001384902,0.00002063674,0.000126854,0.0001047241,0.00004088425],"domain_scores_gemma":[0.9989919,0.0005659592,0.0001728097,0.00008210384,0.0001574111,0.00002976328],"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":[0.00002026395,0.0000145978,0.0002047617,0.00002461079,0.00002200463,0.00002794753,0.0000330175,0.9826318,0.001229128,0.008782636,0.00009799971,0.006911139],"study_design_scores_gemma":[9.478253e-7,0.000004076867,0.00002603625,5.788394e-7,0.000001488906,0.000001196499,0.000001445665,0.9983889,0.0001502742,0.001383937,0.00003957916,0.00000158027],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01168327,0.00005989219,0.9875385,0.00005991156,0.00000936181,0.00001240759,0.0000189785,0.00006234697,0.0005553396],"genre_scores_gemma":[0.9162796,0.000183791,0.08055673,0.00005003913,0.00003163975,0.000149001,0.0001178053,0.00004161624,0.002589771],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01128682,"threshold_uncertainty_score":0.02244228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04170254138005892,"score_gpt":0.3025341573391117,"score_spread":0.2608316159590527,"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."}}