{"id":"W2522549066","doi":"10.1002/cjce.22692","title":"Run‐to‐run optimization of batch processes with self‐optimizing control strategy","year":2016,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Ningbo; National Natural Science Foundation of China","keywords":"Computer science; Process (computing); Mathematical optimization; Batch processing; Control (management); Control variable; Dynamic programming; Nonlinear programming; Batch reactor; Nonlinear system; Control theory (sociology); Algorithm; Mathematics; Artificial intelligence; Machine learning","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":[0.0001588906,0.0001721308,0.0002935045,0.0001674079,0.00003112289,0.00003341104,0.0002547124,0.00007448212,0.00001487795],"category_scores_gemma":[0.0002275222,0.0001082958,0.00004224246,0.0003238782,0.00002808147,0.0002560635,0.000004493196,0.0001491509,0.000001257485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002681621,"about_ca_system_score_gemma":0.0003252236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000586881,"about_ca_topic_score_gemma":0.00009850066,"domain_scores_codex":[0.9990036,0.00001029098,0.0004108754,0.00008630761,0.0001819612,0.0003069685],"domain_scores_gemma":[0.9988959,0.0001639214,0.0001214224,0.0001482583,0.0003355095,0.0003349513],"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":[0.00001625092,0.000002360413,0.00003462514,0.000080431,0.00008078774,0.000007151961,0.0001307798,0.9611821,0.03814374,0.00005736858,0.00002440295,0.0002400673],"study_design_scores_gemma":[0.002803669,0.000183895,0.00003825025,0.001432275,0.0001550842,0.0002716375,0.0000437735,0.9012805,0.0928775,0.0000420068,0.0003183968,0.000553003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04003059,0.0004375677,0.9586458,0.0003001212,0.0001321672,0.0002185759,0.0000122169,0.00007286821,0.0001500581],"genre_scores_gemma":[0.9830394,0.000009587322,0.01672205,0.00001663704,0.0001423552,0.000008335608,6.935207e-7,0.00005414336,0.000006771231],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9430088,"threshold_uncertainty_score":0.4416176,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003607974981395456,"score_gpt":0.1631356653172685,"score_spread":0.1595276903358731,"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."}}