{"id":"W1970596070","doi":"10.1115/detc2008-49702","title":"A Hybrid Relationship Modeling Scheme for Parametric Design Considering Uncertainties","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Parametric statistics; Mathematical optimization; Computer science; Fuzzy logic; Scheme (mathematics); Design of experiments; Optimal design; Mathematics; Artificial intelligence; Machine learning; Statistics","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":[0.0002283467,0.00014204,0.0001554996,0.0002791001,0.0004039084,0.0000650399,0.0003030672,0.00003710304,0.000006316925],"category_scores_gemma":[0.001101441,0.0001410195,0.00006158701,0.0005473186,0.00004963202,0.0007902658,0.00009080246,0.0001021567,0.00001826049],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009111664,"about_ca_system_score_gemma":0.0001340779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001016956,"about_ca_topic_score_gemma":4.897109e-7,"domain_scores_codex":[0.9988382,0.00004703654,0.0002595081,0.000394335,0.0001852495,0.0002756311],"domain_scores_gemma":[0.9983767,0.0008139712,0.00007702945,0.0003389698,0.000314187,0.00007912541],"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":[0.000004842578,0.00001864086,0.0002144501,0.000003731977,0.00000801107,0.000004905729,0.0001463816,0.9821028,0.00001910928,0.01664294,0.0001102547,0.0007239011],"study_design_scores_gemma":[0.0004425171,0.00003336807,0.00003261876,0.00000621167,0.000002310109,0.00005842119,0.00003257457,0.9835219,0.001102282,0.01451563,0.00006204468,0.0001901184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001940359,0.0001021467,0.9964716,0.0001608903,0.000137093,0.0004596033,0.000001079559,0.0003959129,0.0003312763],"genre_scores_gemma":[0.3611431,0.00001181537,0.6383162,0.00009553512,0.00001720588,0.00006132256,0.000001445507,0.00001061249,0.0003427824],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3592027,"threshold_uncertainty_score":0.5750609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1352086204338177,"score_gpt":0.2961570115339922,"score_spread":0.1609483911001745,"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."}}