{"id":"W2930544921","doi":"10.1002/cjce.23494","title":"Online prediction of quality‐related variables for batch processes using a sequential phase partition method","year":2019,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Beijing Municipality; Beijing Municipal Commission of Education; National Natural Science Foundation of China","keywords":"Partition (number theory); Computer science; Partial least squares regression; Process (computing); Batch processing; Data mining; Phase (matter); Curse of dimensionality; Algorithm; Computation; Mathematics; Machine learning; Chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006802041,0.001010336,0.0007890098,0.000696846,0.0003231791,0.0005883351,0.0007213875,0.0004642511,0.0006671771],"category_scores_gemma":[0.001228538,0.0004467314,0.0007983727,0.0006049826,0.0003639469,0.0006771391,0.0005231699,0.0006568973,0.0001576245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004956113,"about_ca_system_score_gemma":0.0009617602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007771192,"about_ca_topic_score_gemma":0.005000189,"domain_scores_codex":[0.9997601,0.00004861236,0.0000143441,0.00006911991,0.00008069353,0.00002723026],"domain_scores_gemma":[0.9994563,0.0002973082,0.00009147696,0.00003752295,0.00009625894,0.00002110503],"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":[0.0002664996,0.0001020718,0.002814283,0.00006915189,0.0000583414,0.00005540809,0.00006599481,0.9184626,0.01286143,0.001368262,0.0002477754,0.06362826],"study_design_scores_gemma":[0.000002464469,0.00001856225,0.0001708904,7.110461e-7,0.000003634355,0.000002670863,0.000001547807,0.998759,0.0008136266,0.0001822383,0.00004246632,0.000002188877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07270689,0.0001134071,0.9261032,0.00004115378,0.00001386379,0.00004961854,0.00007035564,0.0004276384,0.0004738964],"genre_scores_gemma":[0.843173,0.0001652602,0.1552372,0.00002738102,0.00002224338,0.000140656,0.0002792747,0.00005327814,0.0009017148],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007771192,"threshold_uncertainty_score":0.01545191,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02212902091653188,"score_gpt":0.273227693997461,"score_spread":0.2510986730809291,"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."}}