{"id":"W4249001853","doi":"10.1016/b978-0-12-824372-5.00024-5","title":"Exergy and multiobjective optimization","year":2020,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Multi-objective optimization; Exergy; Mathematical optimization; Engineering optimization; Process engineering; Computer science; Optimization problem; Test functions for optimization; Engineering; Mathematics; Multi-swarm optimization","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":[0.00003971406,0.0002942094,0.0003521574,0.00006276171,0.00005824962,0.00002348898,0.00007864892,0.0002877878,0.000203886],"category_scores_gemma":[0.00002529243,0.0002947939,0.0001163619,0.000007909714,0.00005789916,0.00003527891,0.00006731145,0.0003008641,0.00005664318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007129248,"about_ca_system_score_gemma":0.00002337439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.955293e-7,"about_ca_topic_score_gemma":9.828935e-7,"domain_scores_codex":[0.999078,0.000007930862,0.0002458286,0.0003762433,0.0001539241,0.000138112],"domain_scores_gemma":[0.9995058,0.0000354042,0.0001215597,0.0001716534,0.0000499274,0.0001157038],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000242391,0.000003537972,3.804927e-7,0.00007853324,0.0001433117,0.000009445594,0.0002103138,0.0006308507,0.001375931,0.007954303,0.00002974107,0.9895394],"study_design_scores_gemma":[0.0005811003,0.00008271926,0.000002869578,0.0005859664,0.0004410407,0.00005105197,0.00005666965,0.03360876,0.01435108,0.002757665,0.9461913,0.001289799],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0000248262,0.001167272,0.0009255902,0.0000501354,0.0001373811,0.0002410038,0.0000196048,0.0001473951,0.9972868],"genre_scores_gemma":[0.00283073,0.000181197,0.00504207,0.00008139956,0.0005503726,0.00002516339,0.00003600531,0.0001437964,0.9911093],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9882496,"threshold_uncertainty_score":0.9999504,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01074893478850714,"score_gpt":0.2022682904671025,"score_spread":0.1915193556785953,"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."}}