{"id":"W2085781772","doi":"10.1115/detc2009-87121","title":"Hybrid and Adaptive Metamodel Based Global Optimization","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Metamodeling; Computer science; Benchmark (surveying); Global optimization; Computation; Mathematical optimization; Optimization problem; Process (computing); Identification (biology); Metaheuristic; Algorithm; 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":[0.0008102055,0.0005710821,0.0006516572,0.0005886515,0.0001957326,0.0004822072,0.00093192,0.0005749919,0.001429823],"category_scores_gemma":[0.001148682,0.0002435357,0.000578159,0.0005694621,0.0004243758,0.0008126457,0.0008560944,0.0004675116,0.0002590041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003173853,"about_ca_system_score_gemma":0.0003854783,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008335487,"about_ca_topic_score_gemma":0.001245051,"domain_scores_codex":[0.9996872,0.0001183741,0.00001330391,0.00006443627,0.00009436123,0.00002226272],"domain_scores_gemma":[0.9996341,0.0001921318,0.00003718792,0.00007245513,0.00005344133,0.00001073854],"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":[0.0000438463,0.00003142741,0.000604398,0.00005454995,0.00004803175,0.00002699337,0.00003818565,0.9060488,0.006618532,0.01181934,0.0004659597,0.07419994],"study_design_scores_gemma":[0.000006483416,0.0000249344,0.000136013,0.000004307566,0.00000595471,0.00001151199,0.000005603731,0.9939675,0.001275499,0.003740976,0.000816223,0.000004992505],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00783481,0.00007261901,0.9907176,0.00002075466,0.00000660425,0.00001276706,0.00001869444,0.0002245783,0.001091611],"genre_scores_gemma":[0.4918394,0.0001674886,0.5050001,0.00008760353,0.00001594223,0.0002222663,0.0001932138,0.0001435214,0.002330613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001429823,"threshold_uncertainty_score":0.004783273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01221132657466834,"score_gpt":0.2486364543136461,"score_spread":0.2364251277389777,"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."}}