{"id":"W2789817860","doi":"10.1080/16864360.2018.1441230","title":"Artificial intelligence aided CFD analysis regime validation and selection in feature-based cyclic CAD/CFD interaction process","year":2018,"lang":"en","type":"article","venue":"Computer-Aided Design and Applications","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Deutsche Forschungsgemeinschaft","keywords":"CAD; Computer science; Process (computing); Parametric model; Parametric statistics; Computational fluid dynamics; Computer Aided Design; Domain (mathematical analysis); Engineering drawing; Selection (genetic algorithm); Parametric design; Artificial intelligence; Industrial engineering; Engineering; Programming language","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":[0.000739967,0.0003488577,0.0005680648,0.0009909718,0.000593934,0.0009444814,0.0007354512,0.0006474569,0.002119405],"category_scores_gemma":[0.002147948,0.000278926,0.0006364917,0.0005830878,0.0004409531,0.0005706705,0.0005948654,0.0003583353,0.000350993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006004488,"about_ca_system_score_gemma":0.0009353439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004274777,"about_ca_topic_score_gemma":0.002943536,"domain_scores_codex":[0.999666,0.00007015694,0.00002239969,0.00006039295,0.0001385634,0.00004249738],"domain_scores_gemma":[0.999129,0.0004721547,0.00007456329,0.00008069514,0.0002161962,0.00002741179],"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":[0.0003959217,0.0001710834,0.007770879,0.0001589872,0.00004632528,0.0002660791,0.0002415042,0.7259217,0.03177561,0.006219351,0.001139579,0.2258931],"study_design_scores_gemma":[0.000002956489,0.0000182163,0.0006395399,0.000003774605,0.000004843477,0.00001745048,0.000007847178,0.9955441,0.002995777,0.0004260947,0.0003345928,0.000004770669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2132225,0.000324595,0.7776538,0.0001426259,0.00005567124,0.0001082957,0.0001043531,0.001211537,0.00717667],"genre_scores_gemma":[0.915239,0.00009952404,0.08305982,0.00002762205,0.000009659,0.00007082731,0.0001091254,0.00007353771,0.001310796],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004274777,"threshold_uncertainty_score":0.008499801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02331136928161806,"score_gpt":0.26882487502068,"score_spread":0.2455135057390619,"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."}}