{"id":"W2140057245","doi":"10.1109/coase.2010.5584195","title":"Generative CAD and CAE integration using common data model","year":2010,"lang":"en","type":"article","venue":"","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"CAD; Computer science; Parametric model; Data modeling; Process (computing); Associative property; Software engineering; Parametric statistics; Data mining; Data model (GIS); Engineering drawing; Engineering; Artificial intelligence; 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":[0.001464454,0.001055088,0.001149734,0.002293126,0.0007442166,0.002964703,0.002268791,0.001354773,0.007555742],"category_scores_gemma":[0.004443749,0.001005262,0.00195732,0.001863875,0.001337457,0.002292584,0.004038609,0.00147457,0.00216341],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009073175,"about_ca_system_score_gemma":0.001534998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004019119,"about_ca_topic_score_gemma":0.004214859,"domain_scores_codex":[0.9975923,0.0003523073,0.0001245658,0.0005226854,0.001265377,0.0001429181],"domain_scores_gemma":[0.9980618,0.0004860774,0.00007121079,0.0009301347,0.0003989651,0.00005168531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002223587,0.0003009353,0.003123684,0.0003682919,0.0002068562,0.0006323089,0.001045996,0.3071197,0.04066722,0.1785941,0.006301886,0.4614166],"study_design_scores_gemma":[0.00004361657,0.0001057414,0.0006508941,0.00005309135,0.00006511076,0.0004550146,0.0001295471,0.9036203,0.02458178,0.0338328,0.03638903,0.00007306079],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003359444,0.0000348773,0.9913719,0.00004282574,0.000016595,0.000074023,0.00005098707,0.001530066,0.003519358],"genre_scores_gemma":[0.1544799,0.0001157467,0.8377293,0.000102537,0.00001767936,0.0003293499,0.0007846939,0.0006043574,0.005836466],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007555742,"threshold_uncertainty_score":0.02527648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04191369005665683,"score_gpt":0.2645869305347474,"score_spread":0.2226732404780905,"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."}}