{"id":"W4294770080","doi":"10.2196/36211","title":"Global Variations in Event-Based Surveillance for Disease Outbreak Detection: Time Series Analysis","year":2022,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Université de Bordeaux; Agence Nationale de la Recherche","keywords":"Outbreak; Disease surveillance; Medicine; Public health; Infectious disease (medical specialty); Environmental health; Public health surveillance; Disease; Virology; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002105356,0.000301512,0.0008815082,0.0004321702,0.0005692077,0.00008820529,0.0002137345,0.0000608126,0.0002599647],"category_scores_gemma":[0.0006743003,0.0003232055,0.0002617812,0.003106572,0.0001019035,0.0002016936,0.0001303705,0.0002050923,0.000009418113],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007194512,"about_ca_system_score_gemma":0.002295469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001880483,"about_ca_topic_score_gemma":0.002323907,"domain_scores_codex":[0.9961621,0.0007926769,0.0007664831,0.0008279702,0.0005819038,0.0008688336],"domain_scores_gemma":[0.997143,0.0002804223,0.0003161723,0.0007475967,0.0002430274,0.001269779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001103204,0.0004265527,0.9845374,0.0002849392,0.0001630535,0.00002221096,0.00006120124,0.0006138148,0.000003129429,0.0002150103,0.002465739,0.01010379],"study_design_scores_gemma":[0.002202366,0.0003317014,0.8449528,0.00000508426,0.000008322493,0.00001145737,0.00007470936,0.03354853,1.077702e-7,0.00006808116,0.1185246,0.0002722589],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7200743,0.007925061,0.07269033,0.1388614,0.00141157,0.01198585,0.04382646,0.001779295,0.001445672],"genre_scores_gemma":[0.9903584,0.00004617813,0.0003657429,0.003290102,0.0001150818,0.00153374,0.003873772,0.00003068521,0.0003863021],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2702841,"threshold_uncertainty_score":0.999922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01544351248642537,"score_gpt":0.3043140402252896,"score_spread":0.2888705277388642,"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."}}