{"id":"W2037978336","doi":"10.1109/acc.2010.5530508","title":"Correlation analysis of alarm data and alarm limit design for industrial processes","year":2010,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Suncor Energy Incorporated","keywords":"ALARM; Computer science; Rationalization (economics); Data mining; Correlation; Process (computing); False alarm; Constant false alarm rate; Similarity (geometry); Artificial intelligence; Pattern recognition (psychology); Mathematics; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002165972,0.00005995066,0.0001515837,0.0001217646,0.0000225513,0.0000240701,0.00009088966,0.00009658276,0.00003929738],"category_scores_gemma":[0.0001997101,0.0000526826,0.00002082339,0.000322906,0.00001005702,0.0001198109,0.00001170941,0.0000738247,0.000001543775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003831726,"about_ca_system_score_gemma":0.00001503361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002707665,"about_ca_topic_score_gemma":0.0003063779,"domain_scores_codex":[0.999579,0.000008367034,0.0001661756,0.0001097096,0.00006636549,0.00007037826],"domain_scores_gemma":[0.9995376,0.0001514761,0.0000324761,0.0001980536,0.00004932873,0.00003107982],"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":[0.0006439754,0.0002621756,0.04028233,0.0008492973,0.009891125,0.000002096155,0.001605361,0.5075783,0.1726331,0.001261714,0.03116118,0.2338293],"study_design_scores_gemma":[0.0005001901,0.00002490038,0.0003577968,0.000003535661,0.0003388841,7.753795e-7,0.00005637893,0.9885467,0.002568149,0.00001031797,0.007526048,0.00006637515],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1737847,0.0001199253,0.8234367,0.00005518656,0.0007353278,0.0005791545,0.00009438409,0.0001976179,0.0009969018],"genre_scores_gemma":[0.9989516,0.000008141308,0.0007382411,0.000006177306,0.00008355193,0.00002043535,0.00004454474,0.000008129527,0.0001392007],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8251668,"threshold_uncertainty_score":0.2148334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05204334277185933,"score_gpt":0.255842442701233,"score_spread":0.2037990999293736,"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."}}