{"id":"W2750887226","doi":"10.1093/rheumatology/kex060.109","title":"I109. BONE MARROW LESIONS: CLINICAL OBSERVATIONS AND CORRELATION WITH TISSUE STUDIES","year":2017,"lang":"en","type":"article","venue":"Lara D. Veeken","topic":"Hematological disorders and diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Bone marrow; Pathology; Correlation","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003984631,0.0003777623,0.0004858553,0.0008940698,0.0003417025,0.0004543538,0.0003149495,0.0005463163,0.005744238],"category_scores_gemma":[0.001647354,0.0002097081,0.000190781,0.0007790895,0.0003783826,0.000239189,0.0003995339,0.0003957986,0.002755875],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002208459,"about_ca_system_score_gemma":0.0001633496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001201525,"about_ca_topic_score_gemma":0.001018549,"domain_scores_codex":[0.9996235,0.00006394039,0.0000494882,0.00007992732,0.000118107,0.00006503085],"domain_scores_gemma":[0.9993588,0.0001041698,0.0002684992,0.0000395399,0.0001220319,0.0001069729],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002380562,0.0004846377,0.9055676,0.000242791,0.00005334584,0.02213864,0.000419219,0.0001248739,0.03712455,0.0001544732,0.001372713,0.02993653],"study_design_scores_gemma":[0.000069567,0.001891005,0.9337726,0.00006741263,0.00005271735,0.05617363,0.0002896785,0.0002609791,0.003977192,0.0001566739,0.00326988,0.00001865975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9756181,0.005377638,0.001068213,0.0001943813,0.00004218711,0.0002151566,0.001239811,0.00008635701,0.01615817],"genre_scores_gemma":[0.9959342,0.0005725007,0.0004669826,0.000102644,0.00004503254,0.00005678115,0.0006362278,0.00001265821,0.002172902],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005744238,"threshold_uncertainty_score":0.01921642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.150071271871225,"score_gpt":0.3986741704116274,"score_spread":0.2486028985404024,"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."}}