{"id":"W4389084825","doi":"10.1111/nep.14257","title":"Assessing survival post‐kidney transplantation in Australia: A multivariable prediction model","year":2023,"lang":"en","type":"article","venue":"Nephrology","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Health and Medical Research Council; Medical Research Council","keywords":"Medicine; Kidney transplantation; Proportional hazards model; Cohort; Dialysis; Transplantation; Akaike information criterion; Kidney disease; Confidence interval; Internal medicine; Statistic; Survival analysis; Cohort study; Statistics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001584533,0.0001151763,0.0002182596,0.0002372099,0.00004603102,0.00001517592,0.00003424893,0.0001530447,0.00007815161],"category_scores_gemma":[0.00002182204,0.0001016974,0.00005393983,0.0002984345,0.00002686716,0.0001981518,0.000004482262,0.0001547964,0.0001029625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005045886,"about_ca_system_score_gemma":0.00008986568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003022783,"about_ca_topic_score_gemma":0.00005773493,"domain_scores_codex":[0.9990554,0.00005568878,0.0002497371,0.0002278659,0.0001508593,0.0002604833],"domain_scores_gemma":[0.9996343,0.00007519457,0.00004016907,0.0001048392,0.00004218571,0.0001033092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002860044,0.0006606003,0.7572346,0.001035165,0.0004153006,0.00204157,0.003476523,0.03288902,0.1945876,0.002152862,0.0006827754,0.001963926],"study_design_scores_gemma":[0.00700873,0.0002188591,0.9207255,0.0001603706,0.000188569,0.0001530936,0.0001020509,0.06970575,0.001014166,0.0004625492,0.0001510346,0.000109384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941465,0.000004600308,0.00281215,0.001128097,0.0002087989,0.0002743078,0.00009222332,0.0001339599,0.001199321],"genre_scores_gemma":[0.9954975,0.0000937253,0.001472524,0.0007025826,0.00004818841,0.0000367288,0.001113278,0.00001568931,0.001019792],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1935735,"threshold_uncertainty_score":0.4147099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06315424523530429,"score_gpt":0.3590901802377146,"score_spread":0.2959359350024103,"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."}}