{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.07713635,0.001251374,0.002532902,0.004134099,0.001428742,0.005692114,0.00317826,0.003927109,0.007448112],"category_scores_gemma":[0.2995927,0.0009920709,0.001697604,0.005777367,0.007917603,0.01164267,0.005915641,0.006015927,0.0009743209],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009564798,"about_ca_system_score_gemma":0.002145251,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001593147,"about_ca_topic_score_gemma":0.001631481,"domain_scores_codex":[0.9307854,0.06020518,0.001449857,0.002767527,0.004258792,0.000533296],"domain_scores_gemma":[0.5616542,0.4045742,0.00823057,0.01916338,0.004711143,0.001666559],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002619338,0.0000735959,0.00654623,0.0002683524,0.0003321919,0.00006277341,0.0003142226,0.01008883,0.00007540069,0.8682509,0.003836007,0.1098896],"study_design_scores_gemma":[0.00009148608,0.00006820449,0.001009412,0.00009918349,0.00009951159,0.00006842169,0.00007169273,0.03892675,0.00009376677,0.9566908,0.002754553,0.00002622943],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02767648,0.006276932,0.9337876,0.02066176,0.0005687103,0.0001842227,0.0004829988,0.0003693171,0.009992],"genre_scores_gemma":[0.6092314,0.008373413,0.3662421,0.005349997,0.003822566,0.000806027,0.0004988091,0.000339976,0.005335681],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9228637,"threshold_uncertainty_score":0.4079409,"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."}}