{"id":"W3165794465","doi":"10.1093/ije/dyab094","title":"Syndromic surveillance using monthly aggregate health systems information data: methods with application to COVID-19 in Liberia","year":2021,"lang":"en","type":"article","venue":"International Journal of Epidemiology","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"U.S. National Library of Medicine; National Cancer Institute; Canadian Institutes of Health Research","keywords":"Coronavirus disease 2019 (COVID-19); 2019-20 coronavirus outbreak; Aggregate (composite); Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Aggregate data; Medicine; Environmental health; Pandemic; Geography; Virology; Outbreak; Pathology; Disease; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003857666,0.0005509878,0.0003361879,0.002051201,0.0002673666,0.0012344,0.0006696302,0.000386882,0.001379604],"category_scores_gemma":[0.0113321,0.0003318909,0.0007603847,0.001922024,0.0002206878,0.0006064122,0.001105068,0.0005573058,0.0001704349],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001420879,"about_ca_system_score_gemma":0.001431876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.041671,"about_ca_topic_score_gemma":0.0369632,"domain_scores_codex":[0.9988733,0.0006584193,0.0001276246,0.000194776,0.00009031341,0.00005558665],"domain_scores_gemma":[0.9957173,0.002849074,0.0007272963,0.0002624737,0.0003495261,0.0000942371],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003473655,0.0002970605,0.5102085,0.0005921053,0.000705531,0.0006206477,0.002039344,0.1974823,0.002113398,0.004128375,0.005833716,0.2756316],"study_design_scores_gemma":[0.00005570536,0.0001307699,0.1006126,0.0001506752,0.00009547971,0.0001579337,0.001299687,0.8905293,0.001248413,0.00261035,0.003050832,0.00005826181],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.673163,0.0007665289,0.3024419,0.002537595,0.00008080173,0.0009975936,0.01603332,0.001711666,0.002267577],"genre_scores_gemma":[0.6860279,0.0004818522,0.3076919,0.00009098008,0.00003696958,0.0007609181,0.004339794,0.0000538887,0.0005159109],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.041671,"threshold_uncertainty_score":0.08285689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3830873788411935,"score_gpt":0.5551982425351776,"score_spread":0.1721108636939841,"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."}}