{"id":"W4379967661","doi":"10.34067/kid.0000000000000190","title":"Multiview Clustering to Identify Novel Kidney Donor Phenotypes for Assessing Graft Survival in Older Transplant Recipients","year":2023,"lang":"en","type":"article","venue":"Kidney360","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"QEII Foundation","keywords":"Cluster analysis; Medicine; Cohort; Kidney transplantation; Phenotype; Proportional hazards model; Cluster (spacecraft); Transplantation; Internal medicine; Machine learning; Computer science; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003219697,0.0002272312,0.0004273294,0.0003138763,0.00009389204,0.00006249255,0.0001051586,0.00008953913,0.00005144013],"category_scores_gemma":[0.000137558,0.0001930259,0.0001584221,0.0005203824,0.00001687318,0.000163694,0.00002083698,0.0001191142,0.0001248587],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009102045,"about_ca_system_score_gemma":0.0001055341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001475147,"about_ca_topic_score_gemma":0.0001024439,"domain_scores_codex":[0.998395,0.00003025983,0.0004136521,0.0004144957,0.0003003748,0.00044618],"domain_scores_gemma":[0.9990607,0.0001618278,0.00005922529,0.0002102382,0.0000619168,0.0004461234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001141109,0.00117651,0.9142739,0.003600426,0.0006061116,0.0004333754,0.005521221,0.0003963443,0.05249574,0.0001678305,0.001592613,0.0185948],"study_design_scores_gemma":[0.008902919,0.00009284219,0.980746,0.003461949,0.0001980244,0.00002344932,0.00009239277,0.001597482,0.001635707,0.00002484645,0.00295565,0.0002687084],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9456663,0.00006634815,0.04218042,0.004906725,0.002246752,0.002603065,0.0007964084,0.0003037789,0.001230258],"genre_scores_gemma":[0.9900882,0.0001024525,0.005776666,0.001318872,0.0001170953,0.000200721,0.0007637013,0.00005941655,0.001572835],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06647211,"threshold_uncertainty_score":0.7871367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06248185430728753,"score_gpt":0.3802610460464042,"score_spread":0.3177791917391167,"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."}}