{"id":"W2987603081","doi":"10.1002/cjce.23674","title":"An improved intelligent early warning method based on MWSPCA and its application in complex chemical processes","year":2019,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Warning system; Process (computing); Computer science; ALARM; False alarm; Constant false alarm rate; Fault detection and isolation; Early warning system; Principal component analysis; Automation; Data mining; Artificial intelligence; Real-time computing; Engineering","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":[0.0002677071,0.0001236097,0.0001971675,0.0001464061,0.00001674453,0.0000455302,0.000178447,0.00008074861,0.00001050384],"category_scores_gemma":[0.00008521775,0.000103224,0.00003330813,0.0001921916,0.000008531421,0.00008197103,0.000003348808,0.0003777838,0.000003846295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001832206,"about_ca_system_score_gemma":0.00007471227,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002806493,"about_ca_topic_score_gemma":0.0001163251,"domain_scores_codex":[0.999305,0.00001466563,0.0002686518,0.00009465984,0.000106404,0.0002105831],"domain_scores_gemma":[0.9994398,0.00009172603,0.00004591053,0.0001085868,0.00005570368,0.0002582189],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001497265,0.000004057422,0.0001014393,0.00009839417,0.00001282128,0.000002258327,0.0002269687,0.2879603,0.7094766,0.00003461787,0.000003923593,0.002063683],"study_design_scores_gemma":[0.0002771589,0.0000319449,0.0001189583,0.0000636042,0.000005932184,0.00002247815,0.00001511522,0.8641326,0.1348095,0.00000796643,0.0004093462,0.0001053396],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910941,0.0001844581,0.008217115,0.0001134059,0.0000986401,0.000180906,0.000002446846,0.00003496293,0.00007399265],"genre_scores_gemma":[0.9994629,0.00000100416,0.0003594634,0.00004166695,0.00009497497,0.00001004557,0.00000172182,0.00002584498,0.000002384671],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5761724,"threshold_uncertainty_score":0.4209354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00775527582377331,"score_gpt":0.2146729782622396,"score_spread":0.2069177024384663,"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."}}