{"id":"W2777924017","doi":"10.2196/publichealth.7373","title":"A Smartphone App (AfyaData) for Innovative One Health Disease Surveillance from Community to National Levels in Africa: Intervention in Disease Surveillance","year":2017,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":163,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Disease surveillance; Smartphone app; Public health surveillance; Environmental health; Disease; Intervention (counseling); Smartphone application; Medicine; Public health; Internet privacy; mHealth; Psychological intervention; Computer science; Nursing; Multimedia; Pathology","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.009067073,0.000615647,0.001722353,0.0006815174,0.0009031545,0.0003368257,0.0008905045,0.0001450456,0.00005029613],"category_scores_gemma":[0.01109984,0.0006639695,0.0001711913,0.001211785,0.0003598957,0.0007416749,0.0005886689,0.0008704129,0.00002635014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001192822,"about_ca_system_score_gemma":0.00399884,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004039437,"about_ca_topic_score_gemma":0.02559234,"domain_scores_codex":[0.9920877,0.002055563,0.001784081,0.001321193,0.001056495,0.001694934],"domain_scores_gemma":[0.9917722,0.001112579,0.001082091,0.002038894,0.001021617,0.002972614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002501877,0.001789704,0.9542403,0.001397297,0.00006625623,0.0000252953,0.001033012,0.000008751729,0.00001176307,0.0004878463,0.008221997,0.03021595],"study_design_scores_gemma":[0.006789887,0.0003713737,0.9566563,0.0004256082,8.641379e-7,0.000002109721,0.0002338222,0.0007884832,3.960644e-7,0.000678358,0.03351061,0.0005422213],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8846762,0.003654711,0.002250066,0.07748225,0.0005378118,0.006057811,0.02473691,0.0002776061,0.0003266697],"genre_scores_gemma":[0.9851804,0.0003472753,0.0008543839,0.004946407,0.0002793798,0.001314483,0.006811954,0.00008480337,0.0001809503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1005042,"threshold_uncertainty_score":0.9995812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1243439950746771,"score_gpt":0.3859843105109424,"score_spread":0.2616403154362653,"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."}}