{"id":"W2576679537","doi":"10.1016/j.jclinepi.2016.11.017","title":"The number of primary events per variable affects estimation of the subdistribution hazard competing risks model","year":2017,"lang":"en","type":"article","venue":"Journal of Clinical Epidemiology","topic":"Statistical Methods and Inference","field":"Mathematics","cited_by":105,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sunnybrook Health Science Centre; Institute for Clinical Evaluative Sciences; University of Toronto","funders":"","keywords":"Statistics; Medicine; Estimation; Proportional hazards model; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2101081,0.0008595139,0.00217765,0.00114602,0.0008161911,0.002634327,0.002806308,0.002834307,0.002902809],"category_scores_gemma":[0.6045489,0.0008373887,0.002631086,0.001340181,0.003382984,0.003842427,0.003026848,0.004135168,0.0002282267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001738792,"about_ca_system_score_gemma":0.002456816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002846436,"about_ca_topic_score_gemma":0.002064476,"domain_scores_codex":[0.7722872,0.201314,0.007367163,0.008695777,0.009033459,0.001302505],"domain_scores_gemma":[0.1361645,0.8378704,0.009408074,0.01273753,0.003357715,0.0004617476],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008050364,0.0007794273,0.3080235,0.00197996,0.004257482,0.001750152,0.00188011,0.425198,0.003279742,0.07553474,0.002821115,0.1664454],"study_design_scores_gemma":[0.0009039694,0.002241082,0.06710489,0.0009002778,0.001483534,0.001658217,0.0004212766,0.8151507,0.00781871,0.09750846,0.004554845,0.000253964],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2197626,0.001436268,0.7720652,0.001837995,0.0001682631,0.001041318,0.0003514214,0.0002355888,0.003101402],"genre_scores_gemma":[0.8239787,0.0002930577,0.1733496,0.0005196443,0.00007207342,0.00100942,0.0002062113,0.00008326186,0.0004880237],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7898919,"threshold_uncertainty_score":0.9740773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4802679270120412,"score_gpt":0.5825631537549266,"score_spread":0.1022952267428854,"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."}}