{"id":"W2332671137","doi":"10.1097/ede.0000000000000085","title":"Geographic Disparities in US Mortality","year":2014,"lang":"en","type":"letter","venue":"Epidemiology","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Public Health Ontario; University of Toronto","funders":"","keywords":"Socioeconomic status; Geography; Geocoding; Environmental health; Health equity; Public health; Demography; Geographic information system; Location; Population; Medicine; Gerontology; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.007532148,0.0002896776,0.001383755,0.000242157,0.0003407495,0.00002070076,0.0005931332,0.002154526,0.0005250447],"category_scores_gemma":[0.007658718,0.0002724019,0.0002847931,0.000199492,0.001041112,0.00007651885,0.00007555036,0.002294405,0.0001134858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001689821,"about_ca_system_score_gemma":0.0002897895,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2350918,"about_ca_topic_score_gemma":0.04305585,"domain_scores_codex":[0.9909269,0.005484701,0.000991395,0.0005764171,0.0002440291,0.001776539],"domain_scores_gemma":[0.9901252,0.008824582,0.000349872,0.000478802,0.0000486951,0.0001728786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[8.901249e-7,0.000003636361,0.4859318,0.0001189268,0.00001014708,0.00003189489,0.00006984676,0.000001675076,1.326876e-9,0.01385943,0.499885,0.00008673465],"study_design_scores_gemma":[0.00005998226,0.000007741971,0.3706091,0.00004042128,0.000009709376,0.000001128575,0.00002024787,0.000005621459,8.095685e-9,0.03244543,0.5966333,0.0001672665],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.008118902,0.001443881,0.00004231735,0.9677887,0.002256407,0.0003182312,0.00002863849,0.00009675501,0.01990618],"genre_scores_gemma":[0.008940096,0.002147258,0.00009944844,0.9783701,0.006899315,0.0001039487,0.0001438279,0.00002678381,0.003269171],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.192036,"threshold_uncertainty_score":0.9999728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1330942207562963,"score_gpt":0.4199403527164876,"score_spread":0.2868461319601913,"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."}}