{"id":"W3011340068","doi":"10.1115/1.4046650","title":"Sequential Radial Basis Function-Based Optimization Method Using Virtual Sample Generation","year":2020,"lang":"en","type":"article","venue":"Journal of Mechanical Design","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Beijing Institute of Technology; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Radial basis function; Computer science; Metamodeling; Mathematical optimization; Kriging; Robustness (evolution); Optimization problem; Artificial intelligence; Algorithm; Machine learning; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007882009,0.0007500945,0.001016027,0.0005052458,0.0002552998,0.0004775224,0.0008746819,0.0006929355,0.001774624],"category_scores_gemma":[0.001339278,0.0004015034,0.0006373853,0.0004345091,0.0003907335,0.0006079611,0.0005531658,0.000675839,0.0003730738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003911576,"about_ca_system_score_gemma":0.0007780351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002832853,"about_ca_topic_score_gemma":0.002185852,"domain_scores_codex":[0.9995587,0.0001589522,0.00001844299,0.00006406014,0.0001710915,0.00002869609],"domain_scores_gemma":[0.9994542,0.0002521331,0.00005335257,0.00005921699,0.0001581146,0.00002293436],"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":[0.0001251033,0.00005974371,0.0004770751,0.0001098394,0.00003955433,0.00004340665,0.00003527603,0.8981425,0.008346846,0.004238379,0.001016537,0.08736567],"study_design_scores_gemma":[0.000006097442,0.00001580018,0.00002705926,0.000001696509,0.000001836646,0.000004627599,0.000001195656,0.9989569,0.0004796037,0.0002806414,0.0002225869,0.000002002168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008542469,0.0001187946,0.9900163,0.00004989021,0.00002373973,0.00002884661,0.00001624662,0.000330831,0.0008728405],"genre_scores_gemma":[0.5224597,0.0001446617,0.4748015,0.0001256254,0.0000323656,0.0002500119,0.0001520689,0.000137794,0.001896242],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002832853,"threshold_uncertainty_score":0.005936682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1016809283397594,"score_gpt":0.3123270109360753,"score_spread":0.2106460825963158,"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."}}