{"id":"W3182621217","doi":"10.1136/annrheumdis-2019-eular.7900","title":"SAT0534 MAGNETIC RESONANCE IMAGING MARKERS IMPROVE THE PREDICTION MODEL FOR TOTAL KNEE REPLACEMENT OVER 13 YEARS IN OLDER ADULTS","year":2019,"lang":"en","type":"article","venue":"Annals of the Rheumatic Diseases","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"Medicine; Osteoarthritis; Magnetic resonance imaging; Knee pain; Receiver operating characteristic; WOMAC; Knee replacement; Synovitis; Intraclass correlation; Body mass index; Physical therapy; Arthroplasty; Arthritis; Internal medicine; Surgery; Radiology; Pathology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001811405,0.001193685,0.001055599,0.0006295395,0.0004333819,0.001505658,0.0007476609,0.001312777,0.003373559],"category_scores_gemma":[0.004908567,0.000396742,0.002143193,0.0005912139,0.000191058,0.0007715049,0.0006946235,0.001681985,0.001017814],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002984745,"about_ca_system_score_gemma":0.0005770684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008287897,"about_ca_topic_score_gemma":0.0093869,"domain_scores_codex":[0.9994553,0.0001581643,0.0000718173,0.0001536241,0.00007589862,0.00008524385],"domain_scores_gemma":[0.9981067,0.0007610365,0.0003736355,0.000168811,0.0003487317,0.000241081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001002567,0.0001687663,0.9874194,0.000031838,0.0006327491,0.00009737752,0.00003368842,0.001224623,0.0001936687,0.00005385335,0.001061399,0.008080114],"study_design_scores_gemma":[0.00008135919,0.0005516706,0.9654847,0.00006366309,0.00143109,0.0002750653,0.0002006166,0.02965338,0.0003167133,0.0005563098,0.001353897,0.00003159819],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927865,0.002034511,0.001127429,0.0007311591,0.0002409995,0.00001143418,0.001845609,0.00007294471,0.001149374],"genre_scores_gemma":[0.9968286,0.0003216449,0.0003598296,0.0001136227,0.0001334288,0.000007633664,0.001316725,0.000008762981,0.0009097093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008287897,"threshold_uncertainty_score":0.01647931,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008903861075276102,"score_gpt":0.2481656197184698,"score_spread":0.2392617586431937,"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."}}