{"id":"W2050130253","doi":"10.1016/j.jbiomech.2014.01.047","title":"Development of a computational technique to measure cartilage contact area","year":2014,"lang":"en","type":"article","venue":"Journal of Biomechanics","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"St Joseph's Health Care","funders":"Canadian Institutes of Health Research","keywords":"Cartilage; Joint (building); Contact area; Materials science; Biomedical engineering; Articular cartilage; Contact force; Contact mechanics; Composite material; Finite element method; Anatomy; Osteoarthritis; Structural engineering; Physics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004358526,0.0004523355,0.0004356254,0.0009565372,0.0004334091,0.000742493,0.001254718,0.0007045057,0.002528245],"category_scores_gemma":[0.002028728,0.0004836669,0.0004848664,0.00064048,0.0003762274,0.0005965999,0.000699162,0.0007155464,0.0006537436],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003018804,"about_ca_system_score_gemma":0.001217673,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003180507,"about_ca_topic_score_gemma":0.004371905,"domain_scores_codex":[0.9996951,0.00003081203,0.00001867905,0.00004001841,0.0001995292,0.00001589771],"domain_scores_gemma":[0.9990764,0.0003788883,0.00007980141,0.0001355583,0.000297548,0.00003185413],"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":[0.0001233094,0.0003160284,0.005339216,0.0002301136,0.0001096542,0.0002265644,0.0002674593,0.3656726,0.2082935,0.01937916,0.002617698,0.3974247],"study_design_scores_gemma":[0.000007133431,0.00003211764,0.0007582723,0.000004927377,0.000007249264,0.00007541331,0.0000148483,0.9846612,0.01224358,0.0008600677,0.00132245,0.00001276446],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008639898,0.0000193471,0.9899347,0.00003474917,0.00001893203,0.00004676111,0.00004989062,0.0005186073,0.0007370852],"genre_scores_gemma":[0.1706116,0.00007117252,0.8275188,0.00004095608,0.00001923784,0.0002002674,0.0001555525,0.0001611553,0.001221242],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003180507,"threshold_uncertainty_score":0.008457839,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02241255029941794,"score_gpt":0.2585449664597353,"score_spread":0.2361324161603174,"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."}}