{"id":"W3162664130","doi":"10.1007/s10898-021-01019-w","title":"Integrating $$\\varepsilon $$-dominance and RBF surrogate optimization for solving computationally expensive many-objective optimization problems","year":2021,"lang":"en","type":"article","venue":"Journal of Global Optimization","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph","funders":"National Research Foundation Singapore","keywords":"Mathematical optimization; Surrogate model; Optimization problem; Mathematics; Function (biology); Multi-objective optimization; Evolutionary algorithm; Computer science","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":[0.0006120827,0.0003972849,0.0005935911,0.000211551,0.0004379061,0.000511449,0.0004256757,0.0001875482,0.00002373007],"category_scores_gemma":[0.001591371,0.0004123635,0.0001825285,0.00129013,0.00009408558,0.003216649,0.0002161479,0.00023983,0.000001154873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006736686,"about_ca_system_score_gemma":0.0005731715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005619048,"about_ca_topic_score_gemma":0.000007650618,"domain_scores_codex":[0.9968737,0.0002109316,0.001209293,0.000679165,0.0006173216,0.0004095409],"domain_scores_gemma":[0.9911081,0.0003771115,0.001814033,0.0003002629,0.006199358,0.0002011101],"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":[0.00007527634,0.0001347402,0.000246421,0.00004263201,0.00008225209,0.00002701714,0.0006090081,0.9894968,0.00006219588,0.005604344,0.00006436047,0.003554913],"study_design_scores_gemma":[0.002638848,0.0002849164,0.0002196545,0.0002723129,0.00005909283,0.0004884865,0.0004539255,0.993799,0.0004110954,0.0009502833,0.00003051228,0.0003918647],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004062575,0.0006812835,0.9961787,0.0007924197,0.0008536095,0.000694045,0.00002887331,0.0000928857,0.0002719444],"genre_scores_gemma":[0.03051037,0.0004443193,0.9683933,0.0002945165,0.0001558051,0.00003171381,0.00008656644,0.00003998321,0.00004344206],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03010411,"threshold_uncertainty_score":0.9998328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01190640232656003,"score_gpt":0.2696545108687438,"score_spread":0.2577481085421838,"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."}}