{"id":"W2097723730","doi":"10.1093/aje/kwu263","title":"Point: Clarifying Policy Evidence With Potential-Outcomes Thinking--Beyond Exposure-Response Estimation in Air Pollution Epidemiology","year":2014,"lang":"en","type":"article","venue":"American Journal of Epidemiology","topic":"Air Quality and Health Impacts","field":"Environmental Science","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Women's Health Research Institute","funders":"National Institute of Environmental Health Sciences","keywords":"Causal inference; Psychological intervention; Accountability; Public economics; Clean Air Act; Environmental health; Estimation; Air pollution; Medicine; Political science; Economics; Econometrics","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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.03372491,0.000263596,0.001367541,0.000350378,0.000193601,0.000004120286,0.0004535016,0.0001823673,0.0001184454],"category_scores_gemma":[0.05349768,0.0001895127,0.0001584772,0.0005771886,0.00129603,0.0006067007,0.0001128705,0.0008027285,0.00005705388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006515838,"about_ca_system_score_gemma":0.0001967464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005109364,"about_ca_topic_score_gemma":0.0003214944,"domain_scores_codex":[0.9851065,0.0115468,0.001823782,0.0003751012,0.0002542823,0.0008935744],"domain_scores_gemma":[0.9825616,0.01396325,0.002612474,0.0003825265,0.00004032116,0.0004398296],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002034733,0.00007805516,0.7071181,0.00001749467,0.0000328547,0.00001899078,0.001237427,0.2343138,0.0001375994,0.004631029,0.0007575316,0.04962244],"study_design_scores_gemma":[0.0005671786,0.003200029,0.9406143,0.00014828,0.00002525268,0.0004122852,0.0001849913,0.006727278,0.00001017633,0.04710975,0.000807644,0.0001928601],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6044173,0.0001714051,0.2332249,0.1618496,0.0001167956,0.0001269046,0.000001694527,0.00001608063,0.00007537643],"genre_scores_gemma":[0.853205,0.000143268,0.07536124,0.07114532,0.0001007144,0.000004885426,0.000001667904,0.00001604049,0.0000219207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2487876,"threshold_uncertainty_score":0.9949836,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05084235186898115,"score_gpt":0.3759348579561361,"score_spread":0.3250925060871549,"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."}}