{"id":"W4416142124","doi":"10.1186/s41512-025-00208-5","title":"Performance of clinical prediction models for chronic kidney disease among people with diabetes: external validation using the Canadian Primary Care Sentinel Surveillance Network (CPCSSN)","year":2025,"lang":"en","type":"article","venue":"Diagnostic and Prognostic Research","topic":"Chronic Kidney Disease and Diabetes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates; Alberta Innovates - Health Solutions","keywords":"Kidney disease; Primary care; Predictive modelling; Risk assessment; Disease; MEDLINE","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001581482,0.0001833461,0.0004114987,0.0001663041,0.0005874165,0.00008318082,0.0001598209,0.0001171623,0.0000166979],"category_scores_gemma":[0.004292352,0.0001298,0.0001026502,0.0005404438,0.0004974738,0.0001637271,0.00008787475,0.0003630556,0.0000012205],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000276849,"about_ca_system_score_gemma":0.007164381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001917519,"about_ca_topic_score_gemma":0.001767096,"domain_scores_codex":[0.9975477,0.0002574439,0.0004970829,0.0004471777,0.0005439048,0.0007067204],"domain_scores_gemma":[0.993826,0.004055875,0.0001084572,0.0004102209,0.0008099224,0.0007894996],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002983093,0.00009732512,0.9896232,0.002791208,0.0001057725,0.000005277137,0.00009715362,0.003036046,0.000005372278,0.0001212568,0.001409397,0.00240969],"study_design_scores_gemma":[0.001666113,0.0003844824,0.7879158,0.00290048,0.0002639817,7.198403e-7,0.0000576481,0.2063202,0.00002502307,0.0002053721,0.0001624312,0.00009774164],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906338,0.00481529,0.0004918184,0.0005786093,0.0001638536,0.002538795,0.0002183863,0.00002388945,0.0005355334],"genre_scores_gemma":[0.9973004,0.0006602721,0.0001589141,0.0002456516,0.0004850679,0.00043784,0.0006167136,0.0000257763,0.00006937989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2032842,"threshold_uncertainty_score":0.998464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04343195241264646,"score_gpt":0.3448820834389103,"score_spread":0.3014501310262638,"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."}}