{"id":"W2984095412","doi":"10.22605/rrh5147","title":"Geographic disparities associated with travel to medical care and attendance in programs to prevent/manage chronic illness among middle-aged and older adults in Texas","year":2019,"lang":"en","type":"article","venue":"Rural and Remote Health","topic":"Chronic Disease Management Strategies","field":"Medicine","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de Santé Publique du Québec","funders":"National Center for Injury Prevention and Control; National Center for Chronic Disease Prevention and Health Promotion; Centers for Disease Control and Prevention","keywords":"Attendance; Medicine; Gerontology; Family 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003088055,0.0001114649,0.0001199851,0.0005616621,0.0005294121,0.0004656969,0.0002031765,0.0002103882,0.001803712],"category_scores_gemma":[0.001152507,0.0001049663,0.0001840506,0.0007249909,0.0002382651,0.0003427027,0.000630631,0.0002269475,0.00009703488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000508667,"about_ca_system_score_gemma":0.0006026309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04280939,"about_ca_topic_score_gemma":0.06536236,"domain_scores_codex":[0.9998035,0.00003914054,0.00001967059,0.00004472207,0.00002651214,0.00006650567],"domain_scores_gemma":[0.9992265,0.0001014139,0.0003989688,0.00002663052,0.00006094107,0.0001856476],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003885162,0.00003306887,0.9980252,0.0000102822,0.00001365608,0.00003403948,0.0003804394,0.00003099531,0.00007764914,0.00004065679,0.0001262756,0.001188963],"study_design_scores_gemma":[0.000002637471,0.00002461589,0.9989359,0.000008346575,0.000006400688,0.00003146515,0.0007934662,0.00007279058,0.000009991867,0.00001514102,0.00009813322,0.000001191593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995433,0.00005455394,0.00001321951,0.0000709127,0.000001618056,0.000003371618,0.0001134098,7.071145e-7,0.0001988716],"genre_scores_gemma":[0.9997156,0.00005069902,0.00002364995,0.00002348373,0.000004753342,0.00000422467,0.0001002406,3.550166e-7,0.00007692237],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04280939,"threshold_uncertainty_score":0.08512044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008828701885173306,"score_gpt":0.2589216338713803,"score_spread":0.250092931986207,"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."}}