{"id":"W1986143653","doi":"10.1016/j.jprocont.2011.06.013","title":"Unscented Kalman filter based nonlinear model predictive control of a LDPE autoclave reactor","year":2011,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Autoclave; Kalman filter; Extended Kalman filter; Nonlinear system; Control theory (sociology); Model predictive control; Low-density polyethylene; Nonlinear model; Unscented transform; Materials science; Engineering; Computer science; Invariant extended Kalman filter; Control (management); Composite material; Polyethylene; Metallurgy; Physics; 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":[0.0002935062,0.0002659623,0.0007368234,0.0002631371,0.00002855028,0.00001453113,0.0003010144,0.000154503,0.00003657853],"category_scores_gemma":[0.0002133854,0.0002278936,0.0002073919,0.000180478,0.00004761865,0.0005527896,0.000005660696,0.0003482505,0.000002800754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001208475,"about_ca_system_score_gemma":0.0001739337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003142035,"about_ca_topic_score_gemma":0.00000278692,"domain_scores_codex":[0.9980138,0.00006167827,0.001046064,0.000153189,0.0004198709,0.0003054254],"domain_scores_gemma":[0.997668,0.0001049332,0.0007811569,0.0002194834,0.001059645,0.0001668186],"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":[0.00146494,0.0001373681,0.0007055774,0.0001796416,0.000385536,0.00001769093,0.0005881008,0.9801624,0.01590617,0.00004540838,0.00005805767,0.0003490926],"study_design_scores_gemma":[0.009390999,0.000343972,0.0003088108,0.0002259498,0.0002313211,0.00001693025,0.00007412832,0.9849747,0.003983471,0.0002191184,0.00004146172,0.000189119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01030544,0.0003770535,0.9875703,0.00004947225,0.0002343995,0.0005709571,0.0001120871,0.00009684003,0.0006834423],"genre_scores_gemma":[0.9912657,0.00001063436,0.008303925,0.0001005594,0.0001976125,0.00003521941,0.000003618282,0.00006503228,0.000017731],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9809602,"threshold_uncertainty_score":0.9293231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01182575938018524,"score_gpt":0.2205036336022841,"score_spread":0.2086778742220989,"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."}}