{"id":"W2138888843","doi":"10.1177/003335491012500203","title":"How Healthy Could a State Be?","year":2010,"lang":"en","type":"article","venue":"Public Health Reports","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Population and Public Health","funders":"","keywords":"Demography; Socioeconomic status; Baseline (sea); Population; Medicine; Population health; Regression analysis; Environmental health; Gerontology; 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":[],"consensus_categories":[],"category_scores_codex":[0.001004747,0.000199284,0.0001658481,0.0003650814,0.0004875824,0.001082442,0.0002476835,0.000602838,0.002619612],"category_scores_gemma":[0.004003644,0.00007650055,0.0002902621,0.0003637293,0.000528783,0.001112067,0.0006257611,0.0005841765,0.0002302596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001323588,"about_ca_system_score_gemma":0.001583796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01898684,"about_ca_topic_score_gemma":0.03561264,"domain_scores_codex":[0.9996375,0.0001309966,0.00001211315,0.00006519508,0.00003667017,0.000117434],"domain_scores_gemma":[0.9988455,0.0002749184,0.0003148353,0.00006411524,0.0002556078,0.0002449626],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003330538,0.0003574631,0.8857789,0.0001403847,0.0001727012,0.0001757629,0.001157483,0.01527595,0.0007856158,0.01830008,0.00969209,0.06783048],"study_design_scores_gemma":[0.0001045462,0.000754443,0.8883538,0.0004782919,0.000460651,0.0002676447,0.005471634,0.03570729,0.002307129,0.03317864,0.03283922,0.00007674457],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.965591,0.0006145912,0.003730083,0.0144453,0.0001372538,0.00006852434,0.002126018,0.00007423499,0.01321306],"genre_scores_gemma":[0.9978884,0.0001220334,0.0007595382,0.0002746506,0.00001373428,0.00001727042,0.0002638535,0.000002514168,0.0006580537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01898684,"threshold_uncertainty_score":0.03775269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08904534151471728,"score_gpt":0.3978728291636525,"score_spread":0.3088274876489353,"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."}}