{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.004411075,0.0002638174,0.0006468426,0.0002246413,0.0001161062,0.0001127791,0.0001819997,0.00006554967,0.00007836147],"category_scores_gemma":[0.0002576089,0.0002485112,0.00004887909,0.0006797608,0.00003426867,0.0004421134,0.00005476879,0.0003376366,0.00008492599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009239631,"about_ca_system_score_gemma":0.002824604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003760428,"about_ca_topic_score_gemma":0.0007909046,"domain_scores_codex":[0.9953887,0.001288908,0.0006304889,0.000806829,0.000900154,0.0009848493],"domain_scores_gemma":[0.9971899,0.00009259611,0.0002641328,0.0008817472,0.0002660837,0.001305497],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003723393,0.0005087285,0.9861097,0.0004413672,0.00002857577,0.0000190733,0.0006042127,0.00001745645,0.000009868735,0.0001502576,0.0003125356,0.01142584],"study_design_scores_gemma":[0.003790698,0.001144789,0.9746097,0.00005820848,0.000002570737,0.00000574456,0.001588809,0.01139797,6.995187e-8,0.000006272369,0.007170465,0.0002247573],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920358,0.001682243,0.00002043038,0.001127487,0.0001724181,0.003978385,0.00008288203,0.0002151643,0.0006851631],"genre_scores_gemma":[0.9981057,0.00006819766,0.00001417917,0.0006416452,0.0001157243,0.0003802312,0.0005239831,0.00004096952,0.0001093495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0115001,"threshold_uncertainty_score":0.9999967,"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."}}