{"id":"W4399320983","doi":"10.6000/1929-6029.2024.13.06","title":"Competing Risks Model to Evaluate Dropout Dynamics Among the Type 1 Diabetes Patients Registered with the Changing Diabetes in Children (CDiC) Program","year":2024,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Diabetes Management and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Dropout (neural networks); Type 2 diabetes; Diabetes mellitus; Type 1 diabetes; Medicine; Computer science; Endocrinology; Machine learning","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02026145,0.001474028,0.002168015,0.002315662,0.000824111,0.00178707,0.002398955,0.001817665,0.006804434],"category_scores_gemma":[0.02832172,0.0005142834,0.003794331,0.001367584,0.0007485653,0.001058366,0.001452195,0.003272816,0.0004124306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001468797,"about_ca_system_score_gemma":0.002822327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01811914,"about_ca_topic_score_gemma":0.00682085,"domain_scores_codex":[0.9925491,0.005366239,0.0003045695,0.0007415406,0.0002967406,0.0007418334],"domain_scores_gemma":[0.9635252,0.0317355,0.002006739,0.0008078606,0.001082788,0.0008417855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.005098356,0.001739777,0.507499,0.0008776759,0.004551569,0.001305873,0.001589997,0.3647876,0.0006970484,0.03363232,0.007546259,0.07067457],"study_design_scores_gemma":[0.0001395643,0.0007896788,0.01637691,0.00008772108,0.0005233272,0.0001628389,0.0004081456,0.974381,0.0001393758,0.005687214,0.001262982,0.00004121682],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7495394,0.002738067,0.2371976,0.003017422,0.000603171,0.001034503,0.003207619,0.0004706388,0.002191572],"genre_scores_gemma":[0.9697405,0.0006040185,0.02306025,0.0002042134,0.0001645938,0.0007751199,0.002117543,0.00004547384,0.003288345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02026145,"threshold_uncertainty_score":0.1071541,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06697737605967859,"score_gpt":0.4484875874866793,"score_spread":0.3815102114270008,"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."}}