{"id":"W2141721194","doi":"10.1109/icsmc.2003.1245692","title":"Design flow robustness evaluation","year":2004,"lang":"en","type":"article","venue":"","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Robustness (evolution); Computer science; Reliability engineering; Design flow; Mathematical optimization; Risk analysis (engineering); Control theory (sociology); Engineering; Mathematics; Artificial intelligence; Control (management)","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":[0.005323886,0.001397441,0.0006483949,0.001994221,0.0003083369,0.001223983,0.0005349676,0.0007724561,0.004418208],"category_scores_gemma":[0.0175721,0.0002764761,0.0008507007,0.0003939061,0.0006652714,0.0009810078,0.0008230256,0.0006916912,0.000591141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009033969,"about_ca_system_score_gemma":0.0006715767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005864475,"about_ca_topic_score_gemma":0.0002589698,"domain_scores_codex":[0.9964689,0.001316137,0.0001674614,0.0003371804,0.00144901,0.0002612874],"domain_scores_gemma":[0.9926495,0.004316824,0.0007493857,0.000864463,0.00132915,0.0000907117],"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":[0.0003966324,0.000135905,0.003908631,0.0004608669,0.0001432617,0.0001767884,0.0001668596,0.7379535,0.05056619,0.03789847,0.00120273,0.1669902],"study_design_scores_gemma":[0.00003513022,0.0007856049,0.002213096,0.00009900663,0.00009231127,0.0001686509,0.00008027502,0.9031507,0.06016395,0.02606753,0.00709129,0.00005250645],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05266841,0.0003126916,0.9363438,0.0001533824,0.00003738318,0.0002313891,0.0001523862,0.0007180295,0.009382579],"genre_scores_gemma":[0.8333549,0.0003155328,0.1613914,0.0001087362,0.00003605469,0.0004235985,0.0003879784,0.0002825202,0.003699278],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005323886,"threshold_uncertainty_score":0.02815574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2186283275115473,"score_gpt":0.3702857565994957,"score_spread":0.1516574290879484,"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."}}