{"id":"W2037696238","doi":"10.6000/1929-6029.2013.02.04.5","title":"Snapshot of Statistical Methods Used in Geriatric Cohort Studies: How Do We Treat Missing Data in Publications?","year":2013,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Statistical Methods and Bayesian Inference","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Missing data; Longitudinal data; Computer science; Data set; Data mining; Cohort; Medicine; Cohort study; Snapshot (computer storage); Statistics; Data science; Artificial intelligence; Machine learning; Mathematics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.4749495,0.001231608,0.004230625,0.01241859,0.002227955,0.01033198,0.005326758,0.003502334,0.003483507],"category_scores_gemma":[0.7825534,0.001360156,0.004214213,0.01881741,0.004945756,0.0138401,0.006353764,0.004884223,0.0009191464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002906102,"about_ca_system_score_gemma":0.008721277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002401408,"about_ca_topic_score_gemma":0.003035279,"domain_scores_codex":[0.4868179,0.4189158,0.05044518,0.0133529,0.0289095,0.001558769],"domain_scores_gemma":[0.1470684,0.700998,0.06075395,0.05433403,0.03446946,0.002376191],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001281223,0.0001732249,0.1703855,0.03008343,0.01439333,0.0005698702,0.01480175,0.004388261,0.0005622414,0.06336842,0.04355888,0.6564339],"study_design_scores_gemma":[0.001214659,0.002334859,0.1139741,0.1002104,0.01128491,0.002844122,0.01353349,0.03769333,0.003533597,0.5579416,0.1545687,0.0008662228],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03398446,0.1174232,0.7690458,0.0624341,0.007553781,0.001947739,0.003220886,0.0009507407,0.00343928],"genre_scores_gemma":[0.4467612,0.04259454,0.4754177,0.01652822,0.006168236,0.007977089,0.002724551,0.0006914447,0.00113697],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5250505,"threshold_uncertainty_score":0.6474807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3901992935197678,"score_gpt":0.6153466726185004,"score_spread":0.2251473790987326,"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."}}