{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002662341,0.0001524258,0.0002232395,0.0001710991,0.0000814352,0.00007132452,0.0001762373,0.0001916464,0.000005767952],"category_scores_gemma":[0.0001631702,0.0001121213,0.0001212975,0.0003953224,0.00001740804,0.00006979102,0.000003373715,0.0005875883,0.000001064602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001459459,"about_ca_system_score_gemma":0.0001062252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004070907,"about_ca_topic_score_gemma":0.00003908317,"domain_scores_codex":[0.9991533,0.0000122039,0.0002477748,0.00007408053,0.000142492,0.0003701033],"domain_scores_gemma":[0.999314,0.000127118,0.0000578565,0.00009889351,0.0000828866,0.00031925],"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":[0.00002201044,6.473464e-7,0.00001912539,0.00003621113,0.00003481858,0.00002449791,0.00006000713,0.9837595,0.009806799,0.000004322251,0.003900176,0.002331835],"study_design_scores_gemma":[0.0005956453,0.00001239827,0.000006594312,0.0001393808,0.00001736475,0.00005866245,0.00001511229,0.983166,0.01159183,0.00001671091,0.004251897,0.0001283821],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9373885,0.001099518,0.0495143,0.0031472,0.007579745,0.0006352186,0.00003273757,0.0005230068,0.00007973542],"genre_scores_gemma":[0.9985154,3.923306e-7,0.0001411953,0.00004415774,0.001223752,0.000004337833,0.000007149416,0.00004514288,0.00001852629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06112681,"threshold_uncertainty_score":0.4572174,"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."}}