{"id":"W2963044346","doi":"10.2196/14295","title":"An Electronic Disease Early Warning System in Sana’a Governorate, Yemen: Evaluation Study","year":2019,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Centers for Disease Control and Prevention","keywords":"Representativeness heuristic; Medicine; Flexibility (engineering); Epidemiology; Disease surveillance; Environmental health; Strengths and weaknesses; Public health; Disease control; Medical emergency; Statistics; Nursing; Psychology; Mathematics","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":[0.009654926,0.0007081203,0.0004790202,0.0009280625,0.0008447373,0.001049136,0.0004237369,0.0007680623,0.002604206],"category_scores_gemma":[0.01106665,0.0002380832,0.0007936493,0.001014696,0.0007501438,0.001114782,0.001059723,0.0004676718,0.0002467725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004072359,"about_ca_system_score_gemma":0.004966016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01840968,"about_ca_topic_score_gemma":0.01976829,"domain_scores_codex":[0.9946781,0.003497996,0.0004589472,0.0002068742,0.0005513095,0.0006067482],"domain_scores_gemma":[0.9934936,0.002203966,0.001231821,0.0002906731,0.002164135,0.0006157841],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01277776,0.01922577,0.7970307,0.005131644,0.00130087,0.001008758,0.006453809,0.005907323,0.004052949,0.001041212,0.004377233,0.1416919],"study_design_scores_gemma":[0.003541247,0.07686216,0.8777131,0.001146365,0.001512008,0.0004184282,0.0130016,0.01316657,0.004817841,0.0001670989,0.007555662,0.00009790186],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9964969,0.0003164674,0.0002252516,0.0002434826,0.000009373025,0.0009947619,0.0004112358,0.00001420661,0.001288458],"genre_scores_gemma":[0.9969933,0.0003424229,0.0006425725,0.0001135838,0.00001249627,0.0008845489,0.0006152518,0.00000270917,0.0003931866],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01840968,"threshold_uncertainty_score":0.05106074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02101234731785368,"score_gpt":0.330168356197092,"score_spread":0.3091560088792383,"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."}}