{"id":"W2116381183","doi":"10.1111/milq.12001","title":"Summarizing Social Disparities in Health","year":2013,"lang":"en","type":"article","venue":"Milbank Quarterly","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Canadian Institutes of Health Research; Dalhousie University; Robert Wood Johnson Foundation","keywords":"Socioeconomic status; Health equity; Ethnic group; Race (biology); Race and health; Context (archaeology); Consistency (knowledge bases); Social determinants of health; Demographic economics; Geography; Demography; Political science; Sociology; Health care; Economic growth; Population; Economics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.01801285,0.0009232057,0.001119507,0.01987981,0.002553511,0.004469422,0.001167585,0.001134412,0.005958204],"category_scores_gemma":[0.06258223,0.0002484946,0.00131628,0.0227259,0.00205974,0.003794173,0.008260106,0.001945648,0.0005221507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004722599,"about_ca_system_score_gemma":0.01078293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.024071,"about_ca_topic_score_gemma":0.03507522,"domain_scores_codex":[0.9821078,0.009467003,0.002047637,0.001465578,0.004166767,0.0007451802],"domain_scores_gemma":[0.976582,0.01159281,0.004123764,0.002242143,0.004693862,0.0007654799],"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":[0.00009399096,0.000113648,0.1535509,0.003042928,0.001258716,0.0001719196,0.008648563,0.005743972,0.0003564864,0.1760936,0.09762315,0.5533022],"study_design_scores_gemma":[0.0000449317,0.000216334,0.1649854,0.005685539,0.0008009366,0.0002579516,0.02064126,0.008137921,0.0007755744,0.4560805,0.3422222,0.0001514556],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.2341959,0.07092991,0.1817173,0.2028002,0.007315248,0.002708734,0.09834357,0.001085298,0.2009038],"genre_scores_gemma":[0.8432287,0.02674139,0.08386071,0.01039133,0.003834266,0.001436863,0.02694723,0.0001319263,0.003427643],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.024071,"threshold_uncertainty_score":0.09526223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02464127115928633,"score_gpt":0.326608970570026,"score_spread":0.3019676994107396,"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."}}