{"id":"W2525237094","doi":"10.1053/j.ajkd.2016.07.030","title":"A Dynamic Predictive Model for Progression of CKD","year":2016,"lang":"en","type":"article","venue":"American Journal of Kidney Diseases","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":121,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Sunnybrook Hospital; University of Manitoba; McGill University; Seven Oaks General Hospital","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Intensive care medicine; Internal medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002708974,0.000875215,0.001390539,0.001392562,0.0005283691,0.001764976,0.001863995,0.001554526,0.002670041],"category_scores_gemma":[0.006376201,0.0006091258,0.0009852593,0.000878255,0.0005127877,0.001116833,0.001001991,0.00232651,0.0006538426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001411433,"about_ca_system_score_gemma":0.001573046,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02671483,"about_ca_topic_score_gemma":0.01573743,"domain_scores_codex":[0.9992781,0.0002003992,0.00003760467,0.0002734033,0.00009939592,0.0001111266],"domain_scores_gemma":[0.9974037,0.00187065,0.0001957031,0.0001020664,0.0003205363,0.000107271],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002180834,0.0001405817,0.007212074,0.00004157307,0.0001091185,0.0001093202,0.00005085257,0.956412,0.0003004778,0.005597099,0.002204868,0.02760393],"study_design_scores_gemma":[0.00000968176,0.00001521617,0.0005565253,0.000006180233,0.0000156344,0.00001694966,0.000003444768,0.997093,0.00004082923,0.00206132,0.0001758171,0.000005376786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3182289,0.00193766,0.6607089,0.005012707,0.0004391138,0.0001728789,0.004784002,0.002078348,0.006637431],"genre_scores_gemma":[0.9737374,0.0003866085,0.02002426,0.0001757512,0.0001119472,0.0001374812,0.001334724,0.00004744485,0.004044409],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02671483,"threshold_uncertainty_score":0.05311865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007115750053159445,"score_gpt":0.2986931294053451,"score_spread":0.2915773793521856,"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."}}