{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02353247,0.0004044202,0.0003950515,0.002515417,0.0006552385,0.001521561,0.0006963763,0.0009937173,0.001300911],"category_scores_gemma":[0.03849417,0.0006157318,0.0009887923,0.002514961,0.0007175287,0.002688387,0.002305138,0.000623956,0.0002777978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008849,"about_ca_system_score_gemma":0.002904456,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007610075,"about_ca_topic_score_gemma":0.007733683,"domain_scores_codex":[0.9793227,0.01522612,0.001404291,0.000871807,0.002121588,0.001053457],"domain_scores_gemma":[0.965894,0.01968034,0.007076174,0.002111213,0.003470539,0.001767677],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004402192,0.00157247,0.9854343,0.0001460147,0.00005260201,0.00014101,0.001362441,0.00009318894,0.0001546685,0.00007194191,0.0001034611,0.01042758],"study_design_scores_gemma":[0.0002002076,0.004719109,0.9848511,0.000168887,0.00009980987,0.0004549155,0.006876866,0.001593953,0.000153422,0.00008140194,0.0007755633,0.00002471031],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996915,0.0001611134,0.0005578076,0.0001826361,0.000008106788,0.0008385183,0.0003382862,0.000004436438,0.0009940851],"genre_scores_gemma":[0.9955177,0.0001960972,0.002814692,0.0001052431,0.00002293438,0.000907171,0.0003370359,0.000002390344,0.00009673404],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02353247,"threshold_uncertainty_score":0.1244531,"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."}}