{"id":"W2951242625","doi":"10.1136/annrheumdis-2019-eular.8571","title":"SP0045 CAN IMAGING PREDICT PROGRESSORS?","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":"Montreal Clinical Research Institute","funders":"","keywords":"Medicine; Osteoarthritis; Synovitis; Magnetic resonance imaging; Clinical trial; Joint replacement; Joint effusion; Physical therapy; Intensive care medicine; Physical medicine and rehabilitation; Radiology; Internal medicine; Arthritis; Pathology; Arthroplasty","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":[0.001126112,0.0007735334,0.0007593065,0.001491531,0.0005152455,0.001602511,0.0008811951,0.001985013,0.009443995],"category_scores_gemma":[0.005200376,0.0002598924,0.0006786761,0.0008978042,0.000567785,0.002024976,0.0003845583,0.00160963,0.002742564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003042847,"about_ca_system_score_gemma":0.0006389368,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002636139,"about_ca_topic_score_gemma":0.003699939,"domain_scores_codex":[0.9995682,0.00008708348,0.00008656399,0.00006119496,0.00008869103,0.00010842],"domain_scores_gemma":[0.9978709,0.0005459492,0.0004595768,0.0001059421,0.0006101476,0.0004075024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002233619,0.0002946567,0.8938549,0.0002572048,0.0002401776,0.002857329,0.0001202386,0.0003476746,0.002508648,0.00107435,0.01328724,0.08292405],"study_design_scores_gemma":[0.0005699354,0.002055764,0.9082688,0.001424179,0.001456286,0.02230211,0.002166988,0.004915299,0.004191771,0.00908163,0.04342824,0.0001390381],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8556741,0.03336695,0.002996202,0.02281645,0.002213443,0.0001624845,0.00341581,0.0002443472,0.07911014],"genre_scores_gemma":[0.9789262,0.006901038,0.002456791,0.002030853,0.002047665,0.0000460332,0.002561277,0.00004225481,0.00498774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009443995,"threshold_uncertainty_score":0.03159332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01758475984371834,"score_gpt":0.2791605962742958,"score_spread":0.2615758364305775,"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."}}