{"id":"W2532799306","doi":"10.1093/ndt/gfv177.04","title":"FP405EVALUATION OF BONE MICROARCHITECTURE BY HIGH-RESOLUTION PERIPHERAL QUANTITATIVE COMPUTED TOMOGRAPHY IN PATIENTS WITH CHRONIC KIDNEY DISEASE: COMPARISON WITH TRANSILIAC BONE BIOPSY","year":2015,"lang":"en","type":"article","venue":"Nephrology Dialysis Transplantation","topic":"Medical Imaging and Pathology Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Medicine; Kidney disease; Peripheral; Quantitative computed tomography; Biopsy; Bone biopsy; Radiology; Computed tomography; Pathology; Bone density; Internal medicine; Osteoporosis","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":[0.0003295005,0.0002499209,0.000735134,0.0003818164,0.00006648393,0.000006102327,0.0000528383,0.0001431223,0.00001657245],"category_scores_gemma":[0.00003480928,0.0001871222,0.00007931243,0.0006441565,0.0006215317,0.000090821,0.000003601167,0.0002844025,0.000002135765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008022069,"about_ca_system_score_gemma":0.0002062067,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002185028,"about_ca_topic_score_gemma":0.0003631498,"domain_scores_codex":[0.9979241,0.0003919978,0.0005019565,0.0004116209,0.0004773281,0.0002930142],"domain_scores_gemma":[0.9989612,0.00009680566,0.0002273024,0.0001814603,0.0002899811,0.0002432105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02248849,0.001207066,0.9541814,0.000436638,0.0005820836,0.0000617285,0.006300177,0.004667893,0.007677447,0.00004135361,0.000754229,0.00160151],"study_design_scores_gemma":[0.01963048,0.002949787,0.9673779,0.000289435,0.001931354,0.0000188527,0.0001088511,0.006613959,0.0007361348,0.0000428272,0.00006459779,0.0002358446],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9317689,0.001283879,0.0644955,0.001514815,0.00006361669,0.0005994276,0.000206956,0.00005244516,0.00001448143],"genre_scores_gemma":[0.9894829,0.00005165528,0.005925915,0.000437878,0.00002938693,0.0000579473,0.003987635,0.00002001566,0.000006615411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05856959,"threshold_uncertainty_score":0.7630622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362226513008272,"score_gpt":0.2664867352434782,"score_spread":0.2528644701133955,"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."}}