{"id":"W4401822872","doi":"10.1016/j.ekir.2024.08.015","title":"IMPACT CKD: Holistic Disease Model Projecting 10-Year Population Burdens","year":2024,"lang":"en","type":"article","venue":"Kidney International Reports","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"EVERSANA (Canada)","funders":"MedImmune; London School of Economics and Political Science; AstraZeneca; AstraZeneca UK","keywords":"Medicine; Kidney disease; Population; Renal replacement therapy; Dialysis; Intensive care medicine; Renal function; Gerontology; Environmental health; Internal 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001039362,0.0007920661,0.0007435569,0.0005684681,0.0003584165,0.001116527,0.001146667,0.001114381,0.005913804],"category_scores_gemma":[0.002882887,0.0003963715,0.0009892833,0.0008456808,0.0003906031,0.0007509915,0.001136785,0.0008355886,0.0005652851],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001608394,"about_ca_system_score_gemma":0.001704,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04375979,"about_ca_topic_score_gemma":0.01981869,"domain_scores_codex":[0.9996415,0.0001490638,0.00001414963,0.00008402489,0.00004839236,0.00006278727],"domain_scores_gemma":[0.999145,0.0004721206,0.00009093145,0.00004022165,0.0001706476,0.0000810377],"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":[0.00003577509,0.00001223821,0.003411368,0.00002564504,0.00003751501,0.00003819711,0.00001642862,0.9907712,0.00008422529,0.001353485,0.0008324959,0.003381481],"study_design_scores_gemma":[0.0000167139,0.00002920819,0.001197517,0.0000130807,0.00002553877,0.00004066995,0.00001926678,0.9951801,0.00005989498,0.002534521,0.0008717619,0.00001166629],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6298943,0.001767433,0.3118439,0.003676943,0.0002809896,0.0003565127,0.01785315,0.001417728,0.03290907],"genre_scores_gemma":[0.9592751,0.0005506286,0.03170886,0.0002778771,0.00005122674,0.000252042,0.003356972,0.0000748461,0.004452495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04375979,"threshold_uncertainty_score":0.08701015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02740134994066876,"score_gpt":0.363359208462907,"score_spread":0.3359578585222383,"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."}}