{"id":"W3105603278","doi":"10.1016/j.kint.2020.10.033","title":"Updating the International IgA Nephropathy Prediction Tool for use in children","year":2020,"lang":"en","type":"article","venue":"Kidney International","topic":"Renal Diseases and Glomerulopathies","field":"Medicine","cited_by":73,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; University of British Columbia","funders":"Pirogov Russian National Research Medical University; European Renal Association-European Dialysis and Transplant Association; Radboud Universitair Medisch Centrum; Hacettepe Üniversitesi; Warszawski Uniwersytet Medyczny; Aristotle University of Thessaloniki; Karolinska Institutet; Università degli Studi di Torino; Uniwersytet Warszawski; Ospedale Pediatrico Bambino Gesù; Radboud Universiteit; Canadian Institutes of Health Research; Imperial College London; Michael Smith Health Research BC; Univerzita Karlova v Praze","keywords":"Nephropathy; Medicine; Computational biology; Biology; Endocrinology; Diabetes mellitus","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":[0.004913591,0.001087899,0.001206385,0.003035234,0.0007381763,0.002720433,0.001271808,0.001090177,0.002092186],"category_scores_gemma":[0.0226879,0.0003590033,0.001253921,0.002331828,0.0002801554,0.002263116,0.001574209,0.002604404,0.0008732221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008793184,"about_ca_system_score_gemma":0.003147022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0111376,"about_ca_topic_score_gemma":0.01219799,"domain_scores_codex":[0.9980027,0.0005366475,0.0003313664,0.0002412476,0.0006774557,0.00021069],"domain_scores_gemma":[0.9924949,0.002801295,0.001237865,0.0004267696,0.00242095,0.0006181844],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002750168,0.0001569302,0.8546952,0.0001434664,0.0001856225,0.000258362,0.000228917,0.001461473,0.0003102144,0.0006835057,0.02001573,0.1215855],"study_design_scores_gemma":[0.0002233064,0.0005488696,0.9071854,0.001423558,0.001269349,0.003126594,0.001160384,0.03038103,0.005188192,0.003505194,0.04584758,0.0001405188],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8966744,0.01121397,0.03665502,0.01269259,0.002265427,0.0003675754,0.01446572,0.002166356,0.02349892],"genre_scores_gemma":[0.9272286,0.002933812,0.05907252,0.001439869,0.000515954,0.0002437137,0.006463906,0.0002803386,0.001821263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0111376,"threshold_uncertainty_score":0.0259859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01734662802327801,"score_gpt":0.2598985915811011,"score_spread":0.2425519635578231,"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."}}