{"id":"W2032223178","doi":"10.1080/10255842.2011.564161","title":"Prediction of shape and internal structure of the proximal femur using a modified level set method for structural topology optimisation","year":2011,"lang":"en","type":"article","venue":"Computer Methods in Biomechanics & Biomedical Engineering","topic":"Topology Optimization in Engineering","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Femur; Process (computing); Topology (electrical circuits); Bone remodeling; Consistency (knowledge bases); Coronal plane; Computer science; Geometry; Structural engineering; Mathematics; Anatomy; Geology; Engineering; Medicine","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":[0.000422756,0.0003509958,0.000438696,0.0004318414,0.0002166233,0.0004658254,0.0006441931,0.0008693827,0.001235951],"category_scores_gemma":[0.001285249,0.0004448674,0.0005985179,0.0002776622,0.0004469828,0.0003729426,0.0004246561,0.0005016692,0.0002007961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004408508,"about_ca_system_score_gemma":0.001033429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002520087,"about_ca_topic_score_gemma":0.002878143,"domain_scores_codex":[0.9998882,0.00003046538,0.000005011445,0.00001328236,0.00005350754,0.000009563603],"domain_scores_gemma":[0.9996305,0.0002204607,0.00004213486,0.00003338661,0.00005541011,0.00001805685],"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":[0.000008016396,0.000007067264,0.0002320605,0.00001039883,0.000004104798,0.00001590159,0.000009059103,0.9936447,0.00195577,0.0008771521,0.00004179996,0.003194001],"study_design_scores_gemma":[0.000001672546,0.00000471917,0.00006451563,7.902494e-7,8.500718e-7,0.000004571922,0.000001146381,0.9993206,0.0002942763,0.0002610402,0.00004440585,0.000001465991],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1058588,0.0000585829,0.891759,0.00007770015,0.00001417309,0.00005847104,0.00007185191,0.0002222535,0.001879054],"genre_scores_gemma":[0.7590458,0.0000977088,0.2390404,0.00002184022,0.000007421623,0.0001768591,0.0001438147,0.00007398378,0.001392285],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002520087,"threshold_uncertainty_score":0.005010843,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06659618512090347,"score_gpt":0.3151461859078418,"score_spread":0.2485500007869383,"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."}}