{"id":"W2992272781","doi":"10.1377/hlthaff.2019.00915","title":"Healthy People 2020: Rural Areas Lag In Achieving Targets For Major Causes Of Death","year":2019,"lang":"en","type":"article","venue":"Health Affairs","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Statistics Canada","funders":"National Institutes of Health","keywords":"Rural area; Medicine; Cause of death; Environmental health; Demography; Gerontology; Geography; Disease; Internal medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001702549,0.000141486,0.0005468571,0.000110637,0.0003696812,0.00002420201,0.0002179989,0.0001217724,0.0002481718],"category_scores_gemma":[0.0003640801,0.0001388854,0.0001020448,0.000323674,0.00005019397,0.0001816934,0.00003822723,0.000172391,0.00003381239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004695864,"about_ca_system_score_gemma":0.001853898,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.07096507,"about_ca_topic_score_gemma":0.1674074,"domain_scores_codex":[0.9973727,0.0002619331,0.0006262099,0.000248423,0.0003455531,0.001145196],"domain_scores_gemma":[0.9983718,0.0006145696,0.0002640909,0.0002085117,0.00008015402,0.000460874],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001442412,0.0001010964,0.9316519,0.002242236,0.000007258368,0.000001066294,0.01622973,0.0000191352,0.000001356288,0.04150334,0.006545029,0.001553611],"study_design_scores_gemma":[0.001651851,0.0003995469,0.8396739,0.0004243878,0.000006110305,0.000001349709,0.07949935,0.00008163039,0.000005796378,0.0009217207,0.07704909,0.0002853065],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8745397,0.00468814,0.00007602017,0.1094157,0.001687536,0.002898923,0.0001075823,0.00009564593,0.006490782],"genre_scores_gemma":[0.9932814,0.001240726,0.000717513,0.003870169,0.0002085379,0.0000786703,0.00001967607,0.00002128216,0.0005619795],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1187418,"threshold_uncertainty_score":0.9352214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02035998510983384,"score_gpt":0.3453821443633214,"score_spread":0.3250221592534875,"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."}}