{"id":"W2034562492","doi":"10.1080/03052150903325540","title":"Metamodelling and search using space exploration and unimodal region elimination for design optimization","year":2010,"lang":"en","type":"article","venue":"Engineering Optimization","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Metamodeling; Maxima and minima; Benchmark (surveying); Mathematical optimization; Computation; Reduction (mathematics); Global optimization; Kriging; Computer science; Latin hypercube sampling; Dimensionality reduction; Design space exploration; Subspace topology; Mathematics; Algorithm; Artificial intelligence; Machine learning","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":[0.001355182,0.0008088286,0.0009029516,0.0009809653,0.0003070224,0.0004874674,0.0006080983,0.0005408014,0.001679318],"category_scores_gemma":[0.00235684,0.0003533288,0.0007958331,0.0007755303,0.0005897183,0.0008066003,0.0008087615,0.0008055001,0.0003505681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004142316,"about_ca_system_score_gemma":0.0009632701,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001567114,"about_ca_topic_score_gemma":0.001995686,"domain_scores_codex":[0.9992779,0.0003982864,0.00002464333,0.00007046618,0.0001979427,0.00003073538],"domain_scores_gemma":[0.9990583,0.0006496666,0.00007475702,0.0001079327,0.00009435719,0.00001498128],"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":[0.00007583904,0.00004921357,0.0004757793,0.0001428246,0.00005318421,0.00003159422,0.0001012973,0.808587,0.008820185,0.02313647,0.0005888811,0.1579378],"study_design_scores_gemma":[0.00001463907,0.00006541435,0.0001024821,0.00001143124,0.000009609196,0.00002427203,0.00001139463,0.9875975,0.003535449,0.006726321,0.001891284,0.00001013509],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003882505,0.0001041262,0.9953197,0.00002058904,0.000003995202,0.00001721948,0.000008535371,0.0001457063,0.0004976367],"genre_scores_gemma":[0.09536774,0.0001895664,0.9029819,0.00003842609,0.000008251352,0.0002159837,0.0000648176,0.00007792344,0.001055382],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001679318,"threshold_uncertainty_score":0.007166982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04073800279990948,"score_gpt":0.2609161004644074,"score_spread":0.220178097664498,"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."}}