{"id":"W2075199413","doi":"10.1016/j.annepidem.2012.06.105","title":"Accounting for context in studies of health inequalities: a review and comparison of analytic approaches","year":2012,"lang":"en","type":"review","venue":"Annals of Epidemiology","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Confounding; Context (archaeology); Econometrics; Medicine; Statistics; Inequality; Flexibility (engineering); Socioeconomic status; Health equity; Demography; Mathematics; Environmental health; Population; Public health; Geography; Sociology","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":[0.03580083,0.0002190602,0.009281349,0.0001878942,0.00008985803,0.000001335236,0.0002445424,0.0002594987,0.00001132106],"category_scores_gemma":[0.02608152,0.000167196,0.0004196727,0.0002751106,0.0007157815,0.00007558314,0.00007895041,0.0001898137,3.845758e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004324402,"about_ca_system_score_gemma":0.0005799201,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007276296,"about_ca_topic_score_gemma":0.002407898,"domain_scores_codex":[0.9903923,0.004400345,0.004095683,0.0002623182,0.00010956,0.0007398495],"domain_scores_gemma":[0.9737851,0.02146806,0.004199849,0.0002223549,0.0002154667,0.0001091432],"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":[0.000002713769,0.00004114875,0.01020326,0.3751421,0.0001596519,1.780852e-8,0.003067586,1.915336e-7,1.865896e-10,0.06147814,0.002525908,0.5473793],"study_design_scores_gemma":[0.00007441249,0.00009172168,0.00040816,0.04727517,0.0002991381,2.512286e-7,0.008834044,0.000002589274,2.030512e-8,0.0017206,0.9411604,0.0001335367],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00002954835,0.9908084,0.00001993697,0.007462424,0.0001087765,0.001316137,0.00008500472,0.000004229246,0.0001655609],"genre_scores_gemma":[0.001667974,0.9947682,0.0002394285,0.003064899,0.00007113657,0.0001133761,0.00002374608,0.0000114195,0.00003981879],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9386345,"threshold_uncertainty_score":0.9993343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.8909083904649753,"score_gpt":0.6510591461236451,"score_spread":0.2398492443413301,"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."}}