{"id":"W2029617721","doi":"10.1016/j.conengprac.2009.10.003","title":"Development of on-line optimization-based control strategies for a starved-feed semibatch copolymerization reactor","year":2009,"lang":"en","type":"article","venue":"Control Engineering Practice","topic":"Advanced Control Systems Optimization","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"","keywords":"Copolymer; Styrene; Materials science; Nonlinear system; Constraint (computer-aided design); Polymerization; Computer science; Polymer; Chemical engineering; Polymer chemistry; Engineering; Mechanical engineering; Composite material; Physics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003695792,0.0003633965,0.0005072733,0.0002183818,0.00006851272,0.00007694367,0.0001758427,0.0001591411,0.000009224153],"category_scores_gemma":[0.0008186188,0.0003998742,0.0000868283,0.0002916109,0.00001339623,0.0007291287,0.00000271977,0.000178347,0.000003180394],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001910385,"about_ca_system_score_gemma":0.0001752592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002291987,"about_ca_topic_score_gemma":0.000001502446,"domain_scores_codex":[0.998226,0.00003994241,0.0007707416,0.0002814558,0.0002986299,0.0003831816],"domain_scores_gemma":[0.9978865,0.00100426,0.0002837335,0.0003243859,0.0003899412,0.0001111865],"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":[0.0004802853,0.00007696608,9.493627e-7,0.00009288166,0.0001666471,0.000001545544,0.0001492565,0.9719709,0.02413646,0.001202918,0.00002547615,0.001695735],"study_design_scores_gemma":[0.005366161,0.0002083785,0.00001230817,0.00009762764,0.0001185297,0.000002132059,0.00008389185,0.9879263,0.002783978,0.000009378954,0.003025811,0.0003654776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0001823547,0.0003529366,0.9964624,0.0003174009,0.0003527461,0.001185345,0.00005274771,0.0006190544,0.0004750174],"genre_scores_gemma":[0.8594773,0.000009820873,0.1397977,0.0002076154,0.0001321852,0.0001998983,0.00008444088,0.00007836295,0.00001265402],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.859295,"threshold_uncertainty_score":0.9998453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0103440033741866,"score_gpt":0.2424952000766888,"score_spread":0.2321511967025023,"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."}}