{"id":"W1987110068","doi":"10.1002/cjce.21617","title":"Multivariate statistical monitoring of multiphase batch processes with between‐phase transitions and uneven operation durations","year":2011,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Batch processing; Process (computing); Computer science; Multivariate statistics; Mixture model; Statistical process control; Process engineering; Phase (matter); Feature (linguistics); Data mining; Artificial intelligence; Machine learning; Engineering; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009557213,0.00009361225,0.000162197,0.00008865335,0.00004953722,0.00002587143,0.00007453658,0.00004578272,0.0000106824],"category_scores_gemma":[0.00008591824,0.00007072161,0.00002043523,0.0001233111,0.00003851277,0.0001305338,0.0000015839,0.000184142,4.58162e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000512834,"about_ca_system_score_gemma":0.0001276206,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005339496,"about_ca_topic_score_gemma":0.0002732483,"domain_scores_codex":[0.9994432,0.00000969436,0.0002729932,0.00004928176,0.00008825924,0.0001366099],"domain_scores_gemma":[0.9994941,0.00008002042,0.0000385584,0.00006070614,0.00009491287,0.0002316853],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001256281,0.00006621733,0.001601296,0.0008071712,0.0006787468,0.0001517805,0.01323955,0.1965134,0.7807699,0.0007704589,0.0000337785,0.005242039],"study_design_scores_gemma":[0.005955393,0.0004416081,0.003110294,0.0009484373,0.0004312348,0.0007740373,0.0007706948,0.2983887,0.687999,0.00009458054,0.0004019997,0.000684119],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8962822,0.0001737157,0.1031753,0.00005526873,0.0001026784,0.0001026489,0.00005081437,0.00002278719,0.00003453704],"genre_scores_gemma":[0.9964619,0.000002315978,0.003401306,0.000001802914,0.0001053071,0.000006073717,0.000002453322,0.00001698311,0.000001859867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1018753,"threshold_uncertainty_score":0.2883944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01562309677525196,"score_gpt":0.2186624703148415,"score_spread":0.2030393735395896,"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."}}