{"id":"W2036348784","doi":"10.1243/09544054jem1482","title":"Robust design of finned-tube evaporators: A scalable product platform approach","year":2009,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Evaporator; Maximization; Minification; Scalability; Product design; Computer science; Compromise; Product (mathematics); Industrial engineering; Mathematical optimization; Reliability engineering; Engineering; Mathematics; Mechanical engineering","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":[0.0008244613,0.0002670359,0.0005530044,0.0003122192,0.00005176827,0.00002829993,0.001104229,0.0001428088,0.000003220867],"category_scores_gemma":[0.0008477213,0.0001960093,0.0002131126,0.0008015925,0.00005879669,0.001077582,0.0001026248,0.0004867634,2.987813e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001178255,"about_ca_system_score_gemma":0.0001256851,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.669273e-7,"about_ca_topic_score_gemma":1.678544e-8,"domain_scores_codex":[0.9979138,0.000008596849,0.0008869123,0.0002451774,0.0006831539,0.0002623888],"domain_scores_gemma":[0.9977866,0.00005721057,0.0009139655,0.0002275121,0.0008903547,0.0001243014],"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":[0.00004108225,0.0001409101,0.000001895279,0.0001180915,0.00006117694,8.875381e-7,0.0001425934,0.9578385,0.02502079,0.01584224,0.0001553429,0.0006364718],"study_design_scores_gemma":[0.0006331087,0.0002846517,0.00004947947,0.0003072546,0.00004254358,0.00009175442,0.00003304778,0.5399697,0.4575332,0.0006745747,0.0002000836,0.0001806277],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004906854,0.0001784775,0.9937645,0.0002110382,0.0004830779,0.0003290625,0.000003727177,0.00004792638,0.00007540356],"genre_scores_gemma":[0.5764238,0.00003338741,0.4234208,0.00001635383,0.0000805697,0.000002726026,4.791285e-7,0.00001068507,0.00001121692],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5715169,"threshold_uncertainty_score":0.7993028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02088398129636241,"score_gpt":0.208919073836967,"score_spread":0.1880350925406046,"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."}}