{"id":"W4384930620","doi":"10.1142/s0219519423400687","title":"KNEE REPLACEMENT RISK PREDICTION MODELING fOR KNEE OSTEOARTHRITIS USING CLINICAL AND MAGNETIC RESONANCE IMAGE FEATURES: DATA FROM THE OSTEOARTHRITIS INITIATIVE","year":2023,"lang":"en","type":"article","venue":"Journal of Mechanics in Medicine and Biology","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Osteoarthritis; Univariate; Nomogram; WOMAC; Lasso (programming language); Proportional hazards model; Medicine; Feature selection; Magnetic resonance imaging; Artificial intelligence; Computer science; Radiology; Machine learning; Surgery; Internal medicine; Multivariate statistics; Pathology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002836727,0.0002076762,0.0007016513,0.0001943859,0.0001578491,0.00001715243,0.0001428773,0.0002476335,0.00002207545],"category_scores_gemma":[0.001746995,0.0001348509,0.00007214099,0.0002100282,0.000162233,0.0001491968,0.0001845782,0.0005802659,0.000001148226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002990833,"about_ca_system_score_gemma":0.0001143436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004716729,"about_ca_topic_score_gemma":0.0002096117,"domain_scores_codex":[0.9977791,0.0003114454,0.0009845716,0.0004238086,0.0002025039,0.0002985148],"domain_scores_gemma":[0.9979584,0.0009692839,0.0003591766,0.0003708385,0.0002008681,0.0001413964],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"nonrandomized_trial","study_design_scores_codex":[0.005345087,0.0001437337,0.01831541,0.00006518712,0.0001473631,0.0003620936,0.001607914,0.000007449323,0.009884641,0.000842486,0.002028881,0.9612498],"study_design_scores_gemma":[0.2232137,0.3499142,0.01336734,0.01495688,0.005615825,0.006628952,0.03613193,0.1745118,0.0008283505,0.1424492,0.03101153,0.001370238],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9373055,0.05331728,0.004056335,0.002125062,0.001439809,0.001051602,0.0006443848,0.00002507671,0.00003491382],"genre_scores_gemma":[0.9336877,0.04716248,0.01372623,0.001581391,0.003091637,0.00004816294,0.0005833876,0.0000606699,0.00005837502],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9598795,"threshold_uncertainty_score":0.549906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1264883641668743,"score_gpt":0.3762057535415749,"score_spread":0.2497173893747005,"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."}}