{"id":"W2300443037","doi":"10.2196/publichealth.4319","title":"Use of Electronic Health Records and Geographic Information Systems in Public Health Surveillance of Type 2 Diabetes: A Feasibility Study","year":2016,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public health surveillance; Health records; Public health; Environmental health; Geographic information system; Type 2 diabetes; Medicine; Geography; Business; Diabetes mellitus; Cartography; Health care; Political science; Nursing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.009297548,0.0003649463,0.001782161,0.0007652369,0.0001354806,0.0000815579,0.0002066746,0.000122639,0.000011049],"category_scores_gemma":[0.002109257,0.000283362,0.00007958746,0.001638168,0.0002783667,0.0009435075,0.0001320181,0.0003147372,0.000002926199],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005749706,"about_ca_system_score_gemma":0.004958657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002678481,"about_ca_topic_score_gemma":0.004429471,"domain_scores_codex":[0.9924296,0.002286019,0.00223128,0.0007083219,0.0007374462,0.001607399],"domain_scores_gemma":[0.9949182,0.0006066135,0.00138569,0.001036733,0.0006937326,0.00135901],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002309066,0.0006243335,0.9417321,0.00226279,0.00005981945,7.722299e-7,0.0006166493,6.842315e-7,0.000004027095,0.0002091944,0.00073042,0.05352831],"study_design_scores_gemma":[0.002886675,0.00326364,0.9633143,0.0001862268,6.450191e-7,0.000008874812,0.0004423172,0.0002499393,1.160729e-7,0.00001298904,0.02942118,0.0002130868],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770449,0.007228572,0.00007746826,0.01087939,0.0002009053,0.003790185,0.0006275953,0.000118715,0.000032255],"genre_scores_gemma":[0.9921708,0.006018378,0.00005500515,0.001238167,0.00003860632,0.0001360915,0.0002930756,0.00002940851,0.00002043476],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05331522,"threshold_uncertainty_score":0.9999619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04819709387313481,"score_gpt":0.3186054064452497,"score_spread":0.2704083125721149,"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."}}