{"id":"W2107843102","doi":"10.1378/chest.12-1920","title":"The Pros and Cons of Propensity Scores","year":2012,"lang":"en","type":"article","venue":"CHEST Journal","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":84,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hamilton Health Sciences; McMaster University; University of Toronto","funders":"","keywords":"cons; Propensity score matching; Psychology; Data science; Computer science; Statistics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006074203,0.00005805307,0.0001096218,0.00001556747,0.0001423731,0.00002661975,0.00008807599,0.00002919481,0.00001173669],"category_scores_gemma":[0.0006641286,0.00003181419,0.00002142626,0.00003235037,0.0001927613,0.0001665873,0.00004919267,0.0001950178,0.000001537677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001604436,"about_ca_system_score_gemma":0.00002773902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.808411e-7,"about_ca_topic_score_gemma":0.000002352454,"domain_scores_codex":[0.9995021,0.00003505868,0.0001678217,0.00003505857,0.0001045499,0.0001554662],"domain_scores_gemma":[0.999311,0.0002455901,0.00016732,0.0001125705,0.00009281815,0.00007068297],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00009997904,0.0003905424,0.2916847,0.0004343086,0.0001271857,0.00001370676,0.004730103,3.48813e-7,0.07028788,0.5810234,0.01223036,0.03897745],"study_design_scores_gemma":[0.000287008,0.0001460437,0.04604236,0.0001939294,0.00005006963,0.0007712172,0.0003989406,0.00001009472,0.2182129,0.7264988,0.007206909,0.000181653],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841869,0.0006355305,0.01234793,0.0003710845,0.00008907025,0.000223554,0.00000138751,0.0000430342,0.002101498],"genre_scores_gemma":[0.9754985,0.0001484277,0.02412158,0.00001496874,0.00008756982,0.000004139585,6.546325e-8,0.000007521955,0.0001171982],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2456423,"threshold_uncertainty_score":0.1297345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.352589286466483,"score_gpt":0.4242491405310891,"score_spread":0.07165985406460612,"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."}}