{"id":"W2011530951","doi":"10.1002/pamm.201110040","title":"Computational Simulation of Bone Remodeling using Design Space Topology Optimization","year":2011,"lang":"en","type":"article","venue":"PAMM","topic":"Orthopaedic implants and arthroplasty","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Trabecular bone; Computer science; Bone remodeling; Topology optimization; Anisotropy; Enhanced Data Rates for GSM Evolution; Simulation; Biomedical engineering; Topology (electrical circuits); Structural engineering; Physics; Mathematics; Finite element method; Engineering; Artificial intelligence; Osteoporosis; Biology; Optics","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":[0.000530143,0.0003909546,0.00050829,0.0004596465,0.0002875896,0.0004996429,0.0004870886,0.0008375536,0.001965223],"category_scores_gemma":[0.001399092,0.0003349954,0.0004936339,0.0004275679,0.0005718166,0.0002594591,0.0004644514,0.0003494751,0.0001827794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004815889,"about_ca_system_score_gemma":0.0007302226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004642106,"about_ca_topic_score_gemma":0.002802727,"domain_scores_codex":[0.9998516,0.00007212457,0.000005784872,0.00001393001,0.00003954886,0.00001694228],"domain_scores_gemma":[0.9992263,0.0005846865,0.00005258115,0.00004090645,0.00006964343,0.00002587892],"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":[0.0000200077,0.00001007633,0.0002778707,0.00001116225,0.000005355627,0.00001763253,0.00001421137,0.996351,0.0007118625,0.0008597255,0.00005034883,0.00167071],"study_design_scores_gemma":[0.000005134616,0.000006861179,0.00006314606,7.281053e-7,9.514723e-7,0.000002523981,0.000002740871,0.9993652,0.0001895886,0.0002607147,0.0001013721,0.000001218473],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5935301,0.0002342405,0.3935305,0.0003750052,0.00006558009,0.0001563372,0.0004032668,0.0007385392,0.01096657],"genre_scores_gemma":[0.909161,0.00009459801,0.08859101,0.00004134648,0.000009282871,0.0002271514,0.000172472,0.00005888744,0.001644223],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004642106,"threshold_uncertainty_score":0.009230137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09702911375410873,"score_gpt":0.308906030367017,"score_spread":0.2118769166129083,"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."}}