{"id":"W2884888899","doi":"10.1097/01.tp.0000542677.52567.4c","title":"Development and Internal Validation of a Prediction Model for Early Hospital Readmissions in Kidney Transplant Recipients","year":2018,"lang":"en","type":"article","venue":"Transplantation","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University Health Network","funders":"","keywords":"Medicine; Logistic regression; Cohort; Retrospective cohort study; Stepwise regression; Receiver operating characteristic; Internal medicine; Kidney transplantation; Proportional hazards model; Transplantation; Hemodialysis; Emergency medicine; Intensive care medicine","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":[0.0212325,0.001638847,0.001039552,0.001859707,0.0006530645,0.001695023,0.001411657,0.0007111406,0.001233624],"category_scores_gemma":[0.03053985,0.0005240613,0.001480293,0.0007618008,0.0004470842,0.0007683376,0.001280952,0.001245604,0.0004853336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001535675,"about_ca_system_score_gemma":0.003149958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01527626,"about_ca_topic_score_gemma":0.009203293,"domain_scores_codex":[0.9964339,0.002180861,0.00026755,0.0004866028,0.0003925435,0.000238544],"domain_scores_gemma":[0.9809925,0.01384041,0.0009359034,0.0007203497,0.003085518,0.0004252589],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001357385,0.001439228,0.7758887,0.0001223399,0.0008007268,0.0003023657,0.0004718844,0.144378,0.00154624,0.0006927281,0.002365135,0.07063519],"study_design_scores_gemma":[0.00009235981,0.0003597969,0.062549,0.00005782843,0.0001878567,0.00009109663,0.00009966677,0.9345771,0.0009296447,0.0007098684,0.0003183799,0.00002741633],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.931724,0.0001286624,0.06446061,0.0004271167,0.0000478585,0.0005877723,0.001095935,0.0005654595,0.0009626288],"genre_scores_gemma":[0.970883,0.00005132565,0.02712823,0.00005321166,0.00001894565,0.0003215133,0.001294457,0.00002690045,0.000222281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0212325,"threshold_uncertainty_score":0.1122895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02757593488340027,"score_gpt":0.2969042599301547,"score_spread":0.2693283250467544,"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."}}