{"id":"W6983749887","doi":"","title":"New statistical methods for using confounders measured in a validation sample to enhance time-to-event analyses of large databases","year":2017,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Data Analysis with R","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Sample (material); Statistical analysis; Sample size determination; Data collection","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004018666,0.0006761011,0.001399976,0.001195014,0.000631666,0.0003175645,0.002537138,0.0002815015,0.0002479226],"category_scores_gemma":[0.01214308,0.0007401971,0.0003218378,0.001179793,0.00002975828,0.00170188,0.0004200268,0.0004724496,0.00009445124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006665558,"about_ca_system_score_gemma":0.0003931281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003598896,"about_ca_topic_score_gemma":0.004243932,"domain_scores_codex":[0.9939653,0.0009356671,0.001432378,0.001771316,0.001051496,0.0008438916],"domain_scores_gemma":[0.9934036,0.001709443,0.001165053,0.002363236,0.0007882123,0.0005704578],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004425599,0.0003860144,0.00002143226,0.0004890942,0.0007527876,0.00001791407,0.00005134182,0.001515976,0.3140075,0.093294,0.00009309489,0.5889283],"study_design_scores_gemma":[0.001462415,0.0003816207,0.0008271923,0.001419791,0.001147522,0.000006972028,0.0001445688,0.01778199,0.8920394,0.02226696,0.06025892,0.002262677],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02323681,0.000128174,0.9628272,0.00004068371,0.000765442,0.002062799,0.009044806,0.0001418517,0.001752198],"genre_scores_gemma":[0.07485417,0.00001060665,0.9186834,0.0001813689,0.00003474343,0.0001306736,0.004595353,0.0001026004,0.00140707],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5866656,"threshold_uncertainty_score":0.9995049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.102795860233345,"score_gpt":0.4493263950054115,"score_spread":0.3465305347720665,"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."}}