{"id":"W4386479926","doi":"10.1002/cjce.25084","title":"Weighted target feature regression neural networks based soft sensing for industrial process","year":2023,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Autoencoder; Artificial neural network; Artificial intelligence; Pattern recognition (psychology); Feature (linguistics); Computer science; Linear regression; Data mining; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006712765,0.0008298145,0.0006108936,0.0003757386,0.0001772579,0.0004189805,0.0007527633,0.000661734,0.0008958738],"category_scores_gemma":[0.001423686,0.0003386866,0.0007035972,0.0003608779,0.0002630873,0.0009078792,0.0004577523,0.0008826937,0.0002389535],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005347678,"about_ca_system_score_gemma":0.0004451995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004334876,"about_ca_topic_score_gemma":0.003987114,"domain_scores_codex":[0.9996648,0.00006267111,0.00002179477,0.0001093357,0.0001084277,0.00003294784],"domain_scores_gemma":[0.99954,0.000186828,0.00006709684,0.00003728104,0.000158776,0.00001003495],"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":[0.00009799655,0.00006012673,0.000774317,0.00006956077,0.00006372222,0.00006099443,0.00003411826,0.8745503,0.01266667,0.001393692,0.0004083554,0.1098202],"study_design_scores_gemma":[8.795696e-7,0.00001270225,0.00009927708,0.000001583562,0.0000035121,0.00000493299,0.000001076455,0.9984384,0.001166109,0.0002043635,0.00006505146,0.00000211105],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04085851,0.0004204785,0.9565449,0.0001048571,0.00005124235,0.00002361237,0.00004876126,0.0007051447,0.001242395],"genre_scores_gemma":[0.9131151,0.0002527689,0.08381099,0.00009418111,0.00002669045,0.00005497655,0.0001120642,0.00005176502,0.002481449],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004334876,"threshold_uncertainty_score":0.008619249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01044850293363439,"score_gpt":0.2012073088590014,"score_spread":0.190758805925367,"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."}}