{"id":"W192244400","doi":"10.24908/pceea.v0i0.3940","title":"REVIEW OF METAMODELING TECHNIQUES FOR PRODUCT DESIGN WITH COMPUTATION-INTENSIVE PROCESSES","year":2011,"lang":"en","type":"article","venue":"Proceedings of the Canadian Engineering Education Association (CEEA)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metamodeling; Computer science; Computation; Automotive industry; Product (mathematics); Systems engineering; Risk analysis (engineering); Engineering; Software engineering; Business; Algorithm; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.002972824,0.001959708,0.001784496,0.00324331,0.0005061105,0.001766841,0.002735326,0.001452997,0.004051139],"category_scores_gemma":[0.004630762,0.001162857,0.0025746,0.005419677,0.0009562908,0.002436445,0.001044052,0.001934556,0.002277468],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001176563,"about_ca_system_score_gemma":0.002200902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002175302,"about_ca_topic_score_gemma":0.002096308,"domain_scores_codex":[0.9978501,0.0005739626,0.0003685658,0.0002738878,0.0008701695,0.00006349952],"domain_scores_gemma":[0.9973924,0.001517966,0.0002214849,0.0003771032,0.0004568666,0.00003422812],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007151487,0.0001005677,0.000396061,0.01432175,0.0002550806,0.0002602352,0.0004381241,0.08273981,0.009621291,0.1430757,0.0115562,0.7371637],"study_design_scores_gemma":[0.00005420178,0.0001629788,0.0007287587,0.006365157,0.000356655,0.0009498267,0.0001677794,0.08279025,0.01050682,0.1048874,0.7928936,0.0001364973],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.001499326,0.1371679,0.8501129,0.0006812683,0.0003147988,0.0001262526,0.0002499595,0.0006946356,0.009152898],"genre_scores_gemma":[0.02141733,0.2449699,0.7273039,0.0004638153,0.0003951198,0.0003916323,0.0008878864,0.0003935417,0.003776839],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.004051139,"threshold_uncertainty_score":0.01572198,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.018554832752037,"score_gpt":0.210749256646233,"score_spread":0.192194423894196,"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."}}