{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005692176,0.0002643963,0.0002902162,0.0005912709,0.0001966827,0.0003872595,0.0001518832,0.0004118477,0.00119067],"category_scores_gemma":[0.001251559,0.0001479307,0.0002147294,0.0003297306,0.0001916097,0.0002039348,0.0002228532,0.0002508252,0.0002269871],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001588836,"about_ca_system_score_gemma":0.0001206922,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009500857,"about_ca_topic_score_gemma":0.001397563,"domain_scores_codex":[0.9997672,0.00006805217,0.00002607849,0.00005045963,0.00006348437,0.00002462945],"domain_scores_gemma":[0.9993392,0.0001988777,0.0002298842,0.00002961609,0.0001067586,0.00009560417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007469541,0.00003651551,0.9913817,0.0000243784,0.00003722009,0.0001362595,0.0000432039,0.00006648665,0.003107367,0.000009092766,0.00002844167,0.004382354],"study_design_scores_gemma":[0.00002975917,0.000690455,0.9961749,0.00001148417,0.00005157855,0.001239897,0.0001041031,0.000556769,0.0009775794,0.00001994471,0.0001379976,0.000005420197],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987823,0.0005084533,0.0002682318,0.00001647573,0.000003516487,0.000006416082,0.00006301565,0.000007319392,0.0003441811],"genre_scores_gemma":[0.9994879,0.00007963809,0.0002422393,0.00001406744,0.000004821364,0.000005266666,0.00006983353,8.725038e-7,0.00009539889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00119067,"threshold_uncertainty_score":0.00398314,"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."}}