{"id":"W4251753565","doi":"10.32920/ryerson.14648076","title":"Finite element analysis of knee articular cartilage","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Hyperelastic material; Finite element method; Cartilage; Articular cartilage; Osteoarthritis; Ogden; Knee Joint; Structural engineering; Materials science; Deflection (physics); Experimental data; Biomedical engineering; Anatomy; Mathematics; Engineering; Composite material; Medicine; Surgery; Physics","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":[0.0005167668,0.0004700728,0.000573498,0.0007327659,0.000242794,0.000580522,0.0007730412,0.0009736588,0.002707917],"category_scores_gemma":[0.0008994233,0.0003745474,0.0007594954,0.0003398491,0.0003829091,0.0003397967,0.0003816847,0.0004028288,0.001136774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000334422,"about_ca_system_score_gemma":0.0005842168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00191466,"about_ca_topic_score_gemma":0.001442095,"domain_scores_codex":[0.9997432,0.0000518683,0.00002219306,0.00003050108,0.0001307091,0.00002150633],"domain_scores_gemma":[0.9996599,0.0001607182,0.00002912784,0.0000326254,0.0001044053,0.00001330704],"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":[0.00004679512,0.00006196042,0.001065126,0.000336985,0.00004729185,0.0001321907,0.0002097592,0.8630095,0.0884687,0.004899414,0.0005939978,0.04112834],"study_design_scores_gemma":[0.000005726059,0.00003987243,0.0006292032,0.00003350338,0.000008387202,0.00008177368,0.0000348279,0.9884262,0.006601766,0.00114161,0.002982586,0.00001456489],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05473651,0.0005591404,0.9380867,0.0001094275,0.00005801472,0.0001158386,0.0003354771,0.0006199017,0.005378957],"genre_scores_gemma":[0.6398796,0.000932813,0.3441211,0.0001347255,0.00003394283,0.0005765086,0.00114231,0.0003380012,0.01284098],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002707917,"threshold_uncertainty_score":0.009058952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01755461687860707,"score_gpt":0.2666392105088055,"score_spread":0.2490845936301984,"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."}}