{"id":"W2091325390","doi":"10.1108/03321641111168138","title":"A robust objective function for topology optimization","year":2011,"lang":"en","type":"article","venue":"COMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Robustness (evolution); Topology optimization; Topology (electrical circuits); Mathematical optimization; Metric (unit); Computer science; Computational topology; Robust optimization; Mathematics; Engineering; Finite element method","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":[0.003208733,0.001437568,0.001144172,0.001196654,0.0003095194,0.00147664,0.0009320332,0.001305986,0.002359566],"category_scores_gemma":[0.005535577,0.0003255541,0.001289092,0.0009328297,0.001093602,0.001777719,0.001031849,0.00154182,0.0007879156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083669,"about_ca_system_score_gemma":0.001023529,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007951356,"about_ca_topic_score_gemma":0.0003775386,"domain_scores_codex":[0.9980797,0.0007496112,0.0001058734,0.0002862122,0.0006945563,0.00008403943],"domain_scores_gemma":[0.9977981,0.0009937623,0.0003408508,0.000231856,0.0005782463,0.00005728014],"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":[0.00005379672,0.00004042868,0.0004284437,0.0002672013,0.00007244541,0.0000715936,0.00003380553,0.8707822,0.01040242,0.05085902,0.001758428,0.06523021],"study_design_scores_gemma":[0.000005493779,0.00009581425,0.0001633724,0.00003185299,0.00001545513,0.00007088007,0.000009470895,0.9796883,0.00356341,0.01262438,0.003713342,0.00001817995],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001966963,0.0002148668,0.996274,0.0001012253,0.00002506595,0.00002548145,0.00004067759,0.00008059834,0.001270998],"genre_scores_gemma":[0.3238893,0.001144328,0.6681532,0.000264857,0.0001738096,0.0004699227,0.000515727,0.0004135984,0.004975144],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003208733,"threshold_uncertainty_score":0.01696956,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01941786803670501,"score_gpt":0.2321204453402233,"score_spread":0.2127025773035183,"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."}}