{"id":"W2523622649","doi":"10.1016/j.jprocont.2016.08.005","title":"MV benchmark estimation based on high-frequency test signal","year":2016,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China; National Science Foundation","keywords":"Benchmark (surveying); Identifiability; SIGNAL (programming language); Noise (video); Computer science; Multivariable calculus; Control theory (sociology); Variance (accounting); Algorithm; Test data; Control (management); Engineering; Artificial intelligence; Control engineering; Machine learning","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":[0.000281365,0.0001434784,0.0002748423,0.0001802421,0.00004294236,0.00004055818,0.0001546519,0.00007853892,0.0001859355],"category_scores_gemma":[0.0002564224,0.00009078661,0.00009904263,0.0001216802,0.00001671221,0.0002708732,0.000001349901,0.0001520738,0.00004190511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001128989,"about_ca_system_score_gemma":0.0000621827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002376142,"about_ca_topic_score_gemma":0.000002484521,"domain_scores_codex":[0.9988646,0.00003315399,0.0004797801,0.00008600666,0.0003554641,0.0001810222],"domain_scores_gemma":[0.9990526,0.0003067567,0.0002133905,0.0001047309,0.0002098284,0.0001126508],"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":[0.0006349678,0.0003159825,0.007507007,0.0003742472,0.000295568,0.0001250135,0.0001375649,0.4735553,0.3239919,0.0003775797,0.002505522,0.1901794],"study_design_scores_gemma":[0.01297629,0.001142645,0.005188923,0.0007816413,0.000109602,0.0000940069,0.00002906148,0.963347,0.01367806,0.001393775,0.0008444718,0.0004145714],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2101102,0.0006385236,0.7779902,0.003137757,0.002309861,0.0006003767,0.00005463851,0.0003337572,0.004824645],"genre_scores_gemma":[0.9992093,0.000004287446,0.0001953292,0.0001350531,0.000372286,0.00001667563,3.884305e-7,0.00002147929,0.00004516884],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7890991,"threshold_uncertainty_score":0.370217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003510152707368647,"score_gpt":0.2025124166787053,"score_spread":0.1990022639713366,"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."}}