{"id":"W2579730284","doi":"10.1136/rmdopen-2016-000355","title":"Preliminary validation of the Knee Inflammation MRI Scoring System (KIMRISS) for grading bone marrow lesions in osteoarthritis of the knee: data from the Osteoarthritis Initiative","year":2017,"lang":"en","type":"article","venue":"RMD Open","topic":"Osteoarthritis Treatment and Mechanisms","field":"Medicine","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta Hospital; Alberta Hospital Edmonton","funders":"","keywords":"Medicine; Osteoarthritis; Grading (engineering); Bone marrow; Inflammation; Magnetic resonance imaging; Scoring system; Physical therapy; Pathology; Radiology; Internal medicine; Alternative medicine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008041264,0.0002057712,0.0004781998,0.00005533387,0.0006687252,0.0001406223,0.001175654,0.0001241542,0.00002375437],"category_scores_gemma":[0.0006446051,0.0001269022,0.0001320456,0.000147377,0.0001620124,0.0008006938,0.001327844,0.0002001747,0.000006767888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008959994,"about_ca_system_score_gemma":0.000191268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006071306,"about_ca_topic_score_gemma":0.001479093,"domain_scores_codex":[0.998132,0.0002387443,0.0006242607,0.0003836193,0.0003757022,0.0002456765],"domain_scores_gemma":[0.9964473,0.0003976459,0.0007902533,0.002157755,0.0001541905,0.00005282426],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.005314948,0.0006121509,0.1592933,0.001556986,0.0004266822,0.0001170106,0.01616291,0.00010065,0.159099,0.01267419,0.002161932,0.6424803],"study_design_scores_gemma":[0.04749139,0.005958861,0.2603722,0.03491878,0.001454891,0.0001654406,0.01490664,0.001068773,0.6260093,0.003743053,0.00312765,0.000782997],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865104,0.0009896692,0.00009721073,0.001935814,0.0007654061,0.0064988,0.0009568064,0.00002035295,0.002225528],"genre_scores_gemma":[0.9981107,0.00005375311,0.0005930651,0.00003870318,0.0002009501,0.0003930972,0.0003351501,0.00003507915,0.0002395118],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6416973,"threshold_uncertainty_score":0.5174921,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06986986484168489,"score_gpt":0.3100389811471705,"score_spread":0.2401691163054856,"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."}}