{"id":"W2972273052","doi":"10.1007/s00158-019-02372-x","title":"Modified element stacking method for multi-material topology optimization with anisotropic materials","year":2019,"lang":"en","type":"article","venue":"Structural and Multidisciplinary Optimization","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":false,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; General Motors of Canada","keywords":"Topology optimization; Interpolation (computer graphics); Topology (electrical circuits); Isotropy; Mathematical optimization; Computer science; Finite element method; Algorithm; Mathematics; Structural engineering; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003990055,0.0007595507,0.0009890816,0.0009040948,0.0005618187,0.0005988668,0.001548823,0.001379967,0.005536527],"category_scores_gemma":[0.000746573,0.0005211912,0.0007926841,0.0007551656,0.0003811486,0.0007378275,0.0007505685,0.001099425,0.001185569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003523194,"about_ca_system_score_gemma":0.0009014842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001246129,"about_ca_topic_score_gemma":0.003028804,"domain_scores_codex":[0.9997668,0.00006892237,0.000009283612,0.00002126017,0.0001156488,0.00001813031],"domain_scores_gemma":[0.9997136,0.0001228813,0.00002514337,0.00003765235,0.00008308721,0.00001760803],"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":[0.00008525398,0.0001658791,0.0004528062,0.0002110503,0.0001169619,0.0001616926,0.00007409001,0.8483534,0.01511259,0.04180199,0.003147722,0.09031658],"study_design_scores_gemma":[0.000006981435,0.00002225859,0.0000457318,0.000005055364,0.000008441376,0.00001811401,0.000006934462,0.9951692,0.0008580464,0.002433154,0.001421637,0.000004456691],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0139381,0.0002238995,0.9759662,0.00009372499,0.0001302664,0.00006480802,0.00008800921,0.0002468357,0.009248143],"genre_scores_gemma":[0.1945303,0.0002591336,0.7946093,0.0001602243,0.00007706744,0.0004131209,0.0002923322,0.0003896713,0.009268878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005536527,"threshold_uncertainty_score":0.01852155,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01215740568128596,"score_gpt":0.2676816405525601,"score_spread":0.2555242348712741,"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."}}