{"id":"W4383648186","doi":"10.1016/j.procir.2023.02.146","title":"Multi-level design optimization considering uncertainties in configurations and parameters","year":2023,"lang":"en","type":"article","venue":"Procedia CIRP","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Configuration design; Tree (set theory); Mathematical optimization; Node (physics); Function (biology); Optimization problem; Multi-objective optimization; Computer science; Engineering; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002827717,0.000105704,0.000106825,0.0003438527,0.0001262297,0.0001962813,0.00006314331,0.00004342305,0.00002516102],"category_scores_gemma":[0.0004978413,0.0001095139,0.00001130687,0.0006722132,0.00003651116,0.0007946125,0.00004649813,0.00005618402,0.00006487993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001846885,"about_ca_system_score_gemma":0.00003634024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003588073,"about_ca_topic_score_gemma":0.00003436756,"domain_scores_codex":[0.9993085,0.00000681385,0.0001838811,0.0002155741,0.0001013885,0.0001838073],"domain_scores_gemma":[0.9997067,0.00004615046,0.00008001532,0.00006789312,0.0000912972,0.000007957738],"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":[0.0001022832,0.0001130843,0.09667543,0.0007066127,0.000064273,0.00002702936,0.002988725,0.8591439,0.003302855,0.006333325,0.01050925,0.02003324],"study_design_scores_gemma":[0.001128431,0.000004521582,0.04127444,0.00008159486,0.00002504177,0.000001545452,0.001075851,0.9521139,0.00054232,0.002078259,0.001284182,0.0003899042],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5461663,0.000372862,0.4328928,0.008577942,0.002077263,0.003357285,0.000007775753,0.002021101,0.004526681],"genre_scores_gemma":[0.9706064,0.00007227736,0.02820353,0.0004701075,0.0001282638,0.0001192435,0.00009421013,0.00002468876,0.0002813004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4244401,"threshold_uncertainty_score":0.4465846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09388749274125932,"score_gpt":0.2447599265293889,"score_spread":0.1508724337881296,"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."}}