{"id":"W2269782984","doi":"10.6000/1929-6029.2016.05.01.2","title":"Use of Self-Matching to Control for Stable Patient Characteristics While Addressing Time-Varying Confounding on Treatment Effect: A Case Study of Older Intensive Care Patients","year":2016,"lang":"en","type":"article","venue":"International Journal of Statistics in Medical Research","topic":"Intensive Care Unit Cognitive Disorders","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Nursing Research; National Institute on Aging","keywords":"Confounding; Delirium; Medicine; Intensive care unit; Crossover study; Intensive care; Confidence interval; Cohort; Gee; Poisson regression; Cohort study; Generalized estimating equation; Internal medicine; Intensive care medicine; Statistics; Population; Placebo; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0009946688,0.0001789375,0.000663129,0.0009285656,0.00006019361,0.00003076732,0.0001781248,0.00008351877,0.00009619601],"category_scores_gemma":[0.06849841,0.0001137595,0.00009241216,0.0001546049,0.000134246,0.00009531427,0.0000865687,0.0003837804,0.000003276395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001014501,"about_ca_system_score_gemma":0.0004992554,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002604136,"about_ca_topic_score_gemma":0.00004018444,"domain_scores_codex":[0.9955611,0.0004302764,0.001013843,0.0002134282,0.002464206,0.0003172031],"domain_scores_gemma":[0.9402852,0.01052109,0.0004361079,0.0001286549,0.04836273,0.0002662093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.03053658,0.007895875,0.1865804,0.0007819308,0.003803435,0.02983062,0.09232359,0.00010304,0.007954793,0.0004023784,0.003028889,0.6367585],"study_design_scores_gemma":[0.2099383,0.2551191,0.1058026,0.08225435,0.001923733,0.003229596,0.2968579,0.00835284,0.03221018,0.000635169,0.001999856,0.001676374],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9870425,0.00001667476,0.009951899,0.0003510561,0.0004135975,0.0014203,0.0007689724,0.000003545719,0.00003144153],"genre_scores_gemma":[0.998068,0.00002590857,0.001073062,0.0006202408,0.00009184322,0.00004267418,0.00003405014,0.0000297243,0.00001453229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6350821,"threshold_uncertainty_score":0.939348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0670245474532372,"score_gpt":0.4291393783956073,"score_spread":0.3621148309423701,"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."}}