{"id":"W4288886084","doi":"10.1016/j.cmpb.2022.107051","title":"High performance multi-platform computing for large-scale image-based finite element modeling of bone","year":2022,"lang":"en","type":"article","venue":"Computer Methods and Programs in Biomedicine","topic":"Bone health and osteoporosis research","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Bone and Joint Health Institute; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Arthritis Society","keywords":"Computer science; Solver; Computational science; Parallel computing; Speedup; Conjugate gradient method; Central processing unit; Finite element method; von Mises yield criterion; Algorithm; Computer hardware; Structural 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004917163,0.000186132,0.0006770851,0.0004059198,0.0002374613,0.00001383704,0.0001124127,0.00006670971,0.00002167676],"category_scores_gemma":[0.00005592226,0.0001556993,0.00007792524,0.0006046002,0.000102052,0.00004534273,0.000236616,0.0004034226,2.821722e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009205823,"about_ca_system_score_gemma":0.0001314892,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000122806,"about_ca_topic_score_gemma":0.000009821231,"domain_scores_codex":[0.997677,0.0001553417,0.0007972109,0.0003992193,0.0003753963,0.0005958511],"domain_scores_gemma":[0.9987932,0.0003815406,0.0001622317,0.0002700677,0.0001733988,0.0002195726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008600855,0.0009667243,0.01691324,0.002572083,0.00003051168,0.00001378723,0.001055405,0.002547234,0.001297371,0.00002966656,0.00004795442,0.973666],"study_design_scores_gemma":[0.009102152,0.003770149,0.003663529,0.0003218893,0.00003295689,0.00001713776,0.0004923921,0.9792297,0.0004331959,0.00004088361,0.002758331,0.0001376464],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3322189,0.0008644325,0.6647376,0.0006934528,0.0002265116,0.001205722,0.00001584245,0.00003286832,0.000004626997],"genre_scores_gemma":[0.4044057,0.00005179791,0.5946747,0.0004448334,0.0001133716,0.0001147443,0.0001673913,0.00001766959,0.000009817686],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9766825,"threshold_uncertainty_score":0.6349231,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09714088699338001,"score_gpt":0.413347649889555,"score_spread":0.316206762896175,"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."}}