{"id":"W4288709469","doi":"10.1177/09544070221113895","title":"Integrated topology and packaging optimization for conceptual-level electric vehicle chassis design via the component-existence method","year":2022,"lang":"en","type":"article","venue":"Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Chassis; Component (thermodynamics); Powertrain; Topology optimization; Topology (electrical circuits); Electric vehicle; Scalability; Computer science; Domain (mathematical analysis); Engineering; Mechanical engineering; Automotive engineering; Finite element method; Electrical engineering; Mathematics","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":[0.0004811892,0.000578641,0.0004147825,0.0005091818,0.0002105032,0.0006113214,0.0005110401,0.0005419726,0.002632885],"category_scores_gemma":[0.0008389049,0.0004307131,0.0005180392,0.0003167644,0.0004679613,0.0005712773,0.0006115413,0.0005185629,0.0004429825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003538305,"about_ca_system_score_gemma":0.0006138447,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007503387,"about_ca_topic_score_gemma":0.001058859,"domain_scores_codex":[0.999849,0.00005079726,0.000004513035,0.00001857503,0.00006277059,0.00001425803],"domain_scores_gemma":[0.9997978,0.0001097311,0.00002109652,0.00002266785,0.00004080901,0.000008057027],"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":[0.00001622829,0.00002345921,0.0004019205,0.00006881146,0.00001567643,0.00004673455,0.0000445565,0.9469639,0.005474157,0.02215764,0.0003776504,0.02440925],"study_design_scores_gemma":[0.000003798388,0.00002300988,0.00009847635,0.000005804768,0.000004917468,0.00002133048,0.00001117459,0.9941716,0.001127706,0.003076358,0.001452727,0.00000310872],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01266799,0.00007661221,0.9822636,0.00004103353,0.00001186776,0.00002290408,0.00001815283,0.000115833,0.004781975],"genre_scores_gemma":[0.4265141,0.0002512493,0.5666741,0.0000533967,0.0000166377,0.0002540302,0.0001207256,0.0002349786,0.005880733],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002632885,"threshold_uncertainty_score":0.008807898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02061547902844411,"score_gpt":0.2295239589011774,"score_spread":0.2089084798727333,"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."}}