{"id":"W2142994141","doi":"10.1002/aic.11964","title":"A Bayesian approach for control loop diagnosis with missing data","year":2009,"lang":"en","type":"article","venue":"AIChE Journal","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Syncrude (Canada); University of Alberta","funders":"","keywords":"Missing data; Computer science; Bayesian probability; Data mining; Control (management); Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003758287,0.0009037257,0.001645768,0.001870342,0.0005700769,0.001462391,0.001940917,0.001251158,0.001926735],"category_scores_gemma":[0.0163974,0.0009183944,0.000922352,0.0009563453,0.001395577,0.001809177,0.00166357,0.001633227,0.0003161959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275775,"about_ca_system_score_gemma":0.002134741,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003440283,"about_ca_topic_score_gemma":0.002660541,"domain_scores_codex":[0.9976955,0.0008408815,0.0001265347,0.00031586,0.0009052298,0.0001160019],"domain_scores_gemma":[0.9940076,0.004518304,0.0003957602,0.0002203801,0.0007488075,0.0001092001],"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":[0.0001543277,0.00007208706,0.0006297239,0.0002156177,0.0001280558,0.0002145992,0.0001791645,0.8035125,0.002633755,0.08032595,0.0007173917,0.1112168],"study_design_scores_gemma":[0.00001798188,0.00002418488,0.00009660169,0.00001688525,0.00001477179,0.00003397555,0.000007965103,0.9627512,0.000633846,0.03594245,0.0004458409,0.00001432091],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001488824,0.00009670202,0.9978453,0.00009406959,0.0000078354,0.00001548354,0.0000207726,0.00007174088,0.0003592578],"genre_scores_gemma":[0.4165171,0.0004743751,0.5800505,0.0002434458,0.0001455748,0.0003239825,0.0002174566,0.00009242045,0.001935079],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003758287,"threshold_uncertainty_score":0.01987594,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01819296628057209,"score_gpt":0.2387003445244786,"score_spread":0.2205073782439065,"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."}}