{"id":"W3006398448","doi":"10.23919/ituk48006.2019.8996132","title":"A Healthcare Cost Calculator for Older Patients Over the First Year After Renal Transplantation","year":2019,"lang":"en","type":"article","venue":"","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Calculator; Transplantation; Health care; Medicine; Kidney transplantation; Regression; End stage renal disease; Intensive care medicine; Disease; Emergency medicine; Computer science; Surgery; Internal medicine; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001645682,0.0004118994,0.0004449083,0.001816773,0.0002929676,0.0007303753,0.0005725304,0.0002738501,0.001822598],"category_scores_gemma":[0.01052692,0.0001508252,0.0004045599,0.00203609,0.0001115939,0.0003619715,0.0004554895,0.0003562696,0.0002772168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00193109,"about_ca_system_score_gemma":0.002635439,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.063196,"about_ca_topic_score_gemma":0.0799574,"domain_scores_codex":[0.9993024,0.0002391018,0.0001285393,0.00009103819,0.000198833,0.00004010483],"domain_scores_gemma":[0.9950306,0.001419019,0.001649931,0.000216136,0.001472765,0.0002115093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003067546,0.0002760174,0.798161,0.00013283,0.0002112127,0.00009487121,0.0001367265,0.08396385,0.0003241847,0.002032788,0.01800244,0.09635739],"study_design_scores_gemma":[0.0001152126,0.0003403409,0.4779759,0.0001509439,0.0001397913,0.0002539289,0.0002666394,0.5034048,0.001403576,0.001942998,0.01393738,0.00006851123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8882092,0.0007630863,0.05861101,0.002090149,0.000105153,0.0008933371,0.03531392,0.002134806,0.01187942],"genre_scores_gemma":[0.9381116,0.0002396598,0.04970061,0.0001117538,0.00003948566,0.0003055664,0.01040323,0.00005693646,0.001031213],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.063196,"threshold_uncertainty_score":0.1256563,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0121749722147003,"score_gpt":0.2861390839408832,"score_spread":0.2739641117261828,"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."}}