{"id":"W2908053812","doi":"10.1146/annurev-publhealth-040218-043735","title":"Commentary: Causal Inference for Social Exposures","year":2019,"lang":"en","type":"review","venue":"Annual Review of Public Health","topic":"Advanced Causal Inference Techniques","field":"Mathematics","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Causal inference; Observational study; Confounding; Epidemiology; Inference; Social epidemiology; Causal model; Causality (physics); Causal structure; Psychology; Task (project management); Marginal structural model; Cognitive psychology; Medicine; Computer science; Public health; Social determinants of health; Pathology; Artificial intelligence","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.005814861,0.0006856787,0.005708683,0.0002394126,0.0001429619,0.0000310316,0.0009706599,0.0003588968,0.0001247585],"category_scores_gemma":[0.004555187,0.0005397749,0.0009331892,0.0005223707,0.0001509706,0.0003535655,0.00028422,0.000635021,0.00002438584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005115531,"about_ca_system_score_gemma":0.002773616,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005331804,"about_ca_topic_score_gemma":0.00001941668,"domain_scores_codex":[0.9939857,0.001237473,0.002711715,0.0005813634,0.0005736133,0.0009101131],"domain_scores_gemma":[0.9921856,0.002933307,0.00304575,0.0008698417,0.0006851278,0.0002804099],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[3.334665e-7,0.00006103977,3.15979e-7,0.3140267,0.00005397636,2.336211e-7,0.00008631831,2.988689e-10,3.46696e-9,0.04524295,0.1503246,0.4902035],"study_design_scores_gemma":[0.00009372936,0.0003768558,2.90485e-7,0.1130662,0.0002367792,0.000005379542,0.00004912916,1.576824e-7,1.11466e-7,0.008128629,0.8776798,0.0003629732],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[4.787461e-8,0.9723339,0.01376429,0.005517629,0.0001963078,0.005640544,0.001957612,0.0001899925,0.0003996693],"genre_scores_gemma":[5.598209e-7,0.9775318,0.01359592,0.006441959,0.0002901175,0.001026983,0.0008485269,0.0001182782,0.000145865],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7273552,"threshold_uncertainty_score":0.9997054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4879616138877341,"score_gpt":0.5757151415730767,"score_spread":0.08775352768534261,"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."}}