{"id":"W1995742305","doi":"10.1016/j.annepidem.2012.06.027","title":"Estimating Population Benefits Using a Risk Tool: An Example of Diabetes in Canada","year":2012,"lang":"en","type":"article","venue":"Annals of Epidemiology","topic":"Transplantation: Methods and Outcomes","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Public Health Ontario","funders":"","keywords":"Medicine; Hazard ratio; Transplantation; Human leukocyte antigen; Umbilical Cord Blood Transplantation; Internal medicine; Histocompatibility; Cord blood; Allele; Population; Proportional hazards model; Umbilical cord; Gastroenterology; Immunology; Confidence interval; Hematopoietic stem cell transplantation; Antigen; Genetics; Biology","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":[0.009237126,0.0006665654,0.0008825072,0.002066326,0.001892878,0.0021682,0.001315997,0.001306387,0.001435091],"category_scores_gemma":[0.02982171,0.0002038261,0.001099106,0.006979899,0.0008738767,0.0007407244,0.001219583,0.001759658,0.0001041046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01747024,"about_ca_system_score_gemma":0.02765379,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9585929,"about_ca_topic_score_gemma":0.9577801,"domain_scores_codex":[0.9934728,0.00388636,0.0002841447,0.0003157566,0.001504602,0.0005363759],"domain_scores_gemma":[0.9838129,0.01123868,0.0005633612,0.0005549974,0.003257552,0.0005723829],"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":[0.001427885,0.0007888602,0.6441752,0.0007128975,0.001134214,0.001370727,0.003110232,0.104978,0.0005342645,0.02961559,0.01247134,0.1996808],"study_design_scores_gemma":[0.0009445266,0.0008796235,0.5061725,0.001047153,0.001834779,0.001023139,0.009368975,0.4105767,0.001789494,0.03202296,0.03396897,0.0003711109],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8881803,0.004965462,0.04686356,0.01970157,0.0001682425,0.0007792155,0.006572029,0.0002989058,0.03247066],"genre_scores_gemma":[0.9610682,0.001337982,0.03516529,0.0003653765,0.00002992428,0.00007626056,0.0006197616,0.0000328636,0.001304409],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04140711,"threshold_uncertainty_score":0.126756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3362978954577,"score_gpt":0.4383300778305221,"score_spread":0.1020321823728221,"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."}}