{"id":"W2750873313","doi":"10.1515/em-2016-0016","title":"Doubly Robust Estimator for Indirectly Standardized Mortality Ratios","year":2017,"lang":"en","type":"article","venue":"Epidemiologic Methods","topic":"Healthcare Policy and Management","field":"Economics, Econometrics and Finance","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Standardization; Causal inference; Estimator; Outcome (game theory); Context (archaeology); Inference; Statistics; Health care; Quality (philosophy); Econometrics; Case mix index; Standardized mortality ratio; Robust statistics; Medicine; Computer science; Mathematics; Cohort; Economics; Nursing","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":[],"consensus_categories":[],"category_scores_codex":[0.01570083,0.0007323142,0.001495924,0.002899776,0.0003104628,0.001515826,0.002876988,0.001631105,0.01028091],"category_scores_gemma":[0.09350999,0.0004032366,0.001675064,0.001793712,0.001403947,0.002027139,0.002231442,0.002508026,0.001669328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008446987,"about_ca_system_score_gemma":0.001172286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001478489,"about_ca_topic_score_gemma":0.0008606813,"domain_scores_codex":[0.9907984,0.005487395,0.0004352927,0.001231708,0.001643343,0.0004040032],"domain_scores_gemma":[0.9514094,0.03091227,0.006339862,0.006860761,0.004016848,0.000460856],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003579507,0.0002738657,0.03420452,0.0005227088,0.0008282412,0.0003539924,0.0002262091,0.07549307,0.002313025,0.6554588,0.0128487,0.2171189],"study_design_scores_gemma":[0.0002973372,0.0004654615,0.02070957,0.0003362095,0.0004375766,0.0006641856,0.0001476895,0.5406338,0.004756647,0.4129269,0.01846574,0.0001587984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008568754,0.0003413919,0.988224,0.0003641832,0.000110984,0.0001251872,0.000804608,0.0002532977,0.001207512],"genre_scores_gemma":[0.44574,0.001105818,0.5366256,0.0006028594,0.0007140807,0.001465925,0.004899775,0.0002994757,0.008546476],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01570083,"threshold_uncertainty_score":0.08303493,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4825038776388583,"score_gpt":0.498048806669556,"score_spread":0.01554492903069771,"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."}}