{"id":"W4320038101","doi":"10.1016/j.conengprac.2023.105457","title":"False alarm reduction in drilling process monitoring using virtual sample generation and qualitative trend analysis","year":2023,"lang":"en","type":"article","venue":"Control Engineering Practice","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"ALARM; Process (computing); False alarm; Fault detection and isolation; Reduction (mathematics); Computer science; Reliability engineering; Fault (geology); Point (geometry); Sample (material); Constant false alarm rate; Real-time computing; Change detection; Data mining; Engineering; 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":[0.0008757697,0.0004404395,0.000416457,0.001211711,0.0002240459,0.0006118302,0.0004620595,0.0003516375,0.0004255875],"category_scores_gemma":[0.004238646,0.0001974793,0.0003480091,0.0006153519,0.0002762322,0.0007748732,0.0004179583,0.0003492922,0.00009183919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002769112,"about_ca_system_score_gemma":0.0002778913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001030089,"about_ca_topic_score_gemma":0.0008894993,"domain_scores_codex":[0.9994422,0.0001503114,0.00003136222,0.00009842267,0.0002319156,0.00004578599],"domain_scores_gemma":[0.9980087,0.001084166,0.0002219478,0.0001658533,0.0004798909,0.00003945474],"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":[0.001985393,0.0002513419,0.02384849,0.0002596542,0.0001210464,0.0004312695,0.0003940083,0.1959188,0.09218542,0.004297625,0.001298012,0.6790088],"study_design_scores_gemma":[0.0000111308,0.0001446084,0.004148165,0.000005567668,0.00002450741,0.0001094796,0.0000310022,0.9812301,0.0128928,0.001179456,0.0002121028,0.00001118268],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2913847,0.0001810112,0.7061074,0.0001112822,0.00005316392,0.00003407882,0.00008862298,0.001148072,0.0008915649],"genre_scores_gemma":[0.9560611,0.00003562006,0.0436306,0.00001316081,0.000007534559,0.00001071932,0.00004735856,0.00002272555,0.0001713246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001211711,"threshold_uncertainty_score":0.004631579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03130458029135748,"score_gpt":0.3259169272457782,"score_spread":0.2946123469544207,"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."}}