{"id":"W2432824243","doi":"10.1515/ijcre-2016-0041","title":"Conceptual Approach in Multi-Objective Optimization of Packed Bed Membrane Reactor for Ethylene Epoxidation Using Real-coded Non-Dominating Sorting Genetic Algorithm NSGA-II","year":2016,"lang":"en","type":"article","venue":"International Journal of Chemical Reactor Engineering","topic":"Process Optimization and Integration","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Ethylene oxide; Multi-objective optimization; Packed bed; Sorting; Robustness (evolution); Materials science; Process engineering; Engineering; Chemistry; Computer science; Mathematical optimization; Chemical engineering; Algorithm; Mathematics; Polymer; Copolymer; Organic chemistry","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":[0.000318946,0.0002224233,0.0003736755,0.0003830145,0.000009372256,0.00002709519,0.0002582621,0.0001706125,0.00001221811],"category_scores_gemma":[0.001003847,0.0001925724,0.0001331551,0.0001989031,0.00003651576,0.0006176863,0.00003371456,0.0002058494,2.138156e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004991367,"about_ca_system_score_gemma":0.00006653633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001084691,"about_ca_topic_score_gemma":5.232957e-7,"domain_scores_codex":[0.9981415,0.0000180714,0.00104397,0.0001800957,0.0003958818,0.0002204997],"domain_scores_gemma":[0.9982378,0.0002707038,0.0004996012,0.00009275806,0.0008121804,0.00008694541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005000417,0.0000606972,0.00006566769,0.00002996467,0.00008642136,0.000001847465,0.0005814874,0.2291725,0.7665955,0.00004820415,0.000002526643,0.003305142],"study_design_scores_gemma":[0.001235348,0.00002335057,0.0000407613,0.000226586,0.00001583524,0.00001472437,0.00007122499,0.5315392,0.4667026,0.000009474884,0.000004254067,0.0001167203],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3822855,0.00003381239,0.6171954,0.0000148508,0.000263566,0.0001348087,0.0000173626,0.00002777586,0.00002694494],"genre_scores_gemma":[0.6885328,0.00008467993,0.311121,0.000004113822,0.0001747684,0.00001221538,0.0000285526,0.00004044932,0.000001424521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3062473,"threshold_uncertainty_score":0.7852876,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01744368664230565,"score_gpt":0.2598879084551753,"score_spread":0.2424442218128696,"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."}}