{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003308038,0.0001250117,0.0002004566,0.00006356971,0.0001321374,0.0001612569,0.0002414678,0.00006035843,0.00001763753],"category_scores_gemma":[0.0000329987,0.00009545569,0.00004955019,0.00008107688,0.000009139801,0.0002364128,0.000004448884,0.0002188984,0.000003454881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004123375,"about_ca_system_score_gemma":0.00002120371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002899118,"about_ca_topic_score_gemma":0.000003760388,"domain_scores_codex":[0.9992368,0.00002833348,0.0002171619,0.0001276672,0.0001459458,0.0002441314],"domain_scores_gemma":[0.9994614,0.00004999561,0.00005365423,0.000261825,0.00003408374,0.0001390196],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006262541,0.0003284985,0.003717025,0.0001943847,0.001155425,0.00008527909,0.0006126596,0.1702695,0.01045126,0.0001251252,0.08854783,0.7238867],"study_design_scores_gemma":[0.002562411,0.0001710106,0.0004433525,0.00004295784,0.00008312259,0.0004209269,0.0001140867,0.972753,0.0002109935,0.00005724942,0.02295539,0.0001854744],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002169378,0.001146197,0.9934,0.0007429156,0.0001994833,0.0002568908,0.00001639438,0.0001338664,0.001934842],"genre_scores_gemma":[0.9931046,0.00002926847,0.005888679,0.000306697,0.0005501554,0.0000186223,0.000006949647,0.0000231609,0.0000718124],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9909353,"threshold_uncertainty_score":0.389257,"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."}}