{"id":"W4403079215","doi":"10.1002/jor.25984","title":"How accurately do finite element models predict the fall impact response of ex vivo specimens augmented by prophylactic intramedullary nailing?","year":2024,"lang":"en","type":"article","venue":"Journal of Orthopaedic Research®","topic":"Orthopaedic implants and arthroplasty","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Eidgenössische Technische Hochschule Zürich; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Faculty of Medicine, University of British Columbia","keywords":"Intramedullary rod; Ex vivo; Finite element method; Structural engineering; Medicine; Surgery; In vivo; Engineering; Biology","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":[0.001057214,0.000778205,0.0005269887,0.0004793756,0.0001104142,0.0008150468,0.000997054,0.001956763,0.001117927],"category_scores_gemma":[0.004223889,0.0006706704,0.0005444397,0.0002848931,0.0005123619,0.0007400062,0.0003014714,0.0003637804,0.001094603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002525956,"about_ca_system_score_gemma":0.0004954351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001943252,"about_ca_topic_score_gemma":0.003612998,"domain_scores_codex":[0.9995573,0.0001083676,0.00005187385,0.00007760527,0.0001681206,0.00003675868],"domain_scores_gemma":[0.9985999,0.0007416687,0.0001827312,0.0002327103,0.0002141623,0.00002880029],"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":[0.0002601268,0.0002248475,0.02841594,0.0005281951,0.0001191968,0.0002745277,0.0002816029,0.7458478,0.1694583,0.000420992,0.0003011767,0.05386727],"study_design_scores_gemma":[0.00001609322,0.0003611211,0.02038327,0.0001005963,0.00007491309,0.0004240972,0.0003113607,0.9447317,0.0307989,0.0006509174,0.002086385,0.00006065444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7681594,0.001156443,0.2272657,0.0001616107,0.00006859571,0.00009397316,0.0009562551,0.0005625237,0.001575497],"genre_scores_gemma":[0.954057,0.0007154396,0.04363518,0.00005078311,0.000005415692,0.00008528343,0.0006053468,0.00006424688,0.0007812119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001956763,"threshold_uncertainty_score":0.005591094,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06617218274820916,"score_gpt":0.368171575901217,"score_spread":0.3019993931530078,"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."}}