{"id":"W2038697101","doi":"10.1017/s0950268813003464","title":"Emergency department and ‘Google flu trends’ data as syndromic surveillance indicators for seasonal influenza","year":2014,"lang":"en","type":"article","venue":"Epidemiology and Infection","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"Winnipeg Regional Health Authority; University of Manitoba; Manitoba Health","funders":"","keywords":"Medicine; Emergency department; Seasonal influenza; Influenza-like illness; Emergency medicine; Coronavirus disease 2019 (COVID-19); Internal medicine; Disease; Virology; Infectious disease (medical specialty)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.005369348,0.000471144,0.0003620806,0.002989858,0.0001351371,0.0007905504,0.0002646879,0.0002348773,0.0007865364],"category_scores_gemma":[0.01407487,0.0002538331,0.0005323231,0.003623594,0.0002055699,0.0009149566,0.0007164245,0.0003332073,0.0001706429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004007541,"about_ca_system_score_gemma":0.000583579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01525312,"about_ca_topic_score_gemma":0.03278835,"domain_scores_codex":[0.9958587,0.00254636,0.0003246484,0.0002924725,0.0007508809,0.0002268891],"domain_scores_gemma":[0.9902182,0.004202883,0.002973035,0.0004465791,0.001821824,0.0003373458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001546327,0.00001935876,0.9930114,0.00003769531,0.0001477352,0.00001676312,0.00009757662,0.0005811868,0.000176486,0.00007086572,0.0001767948,0.005509566],"study_design_scores_gemma":[0.000008070339,0.000197328,0.9935513,0.00002122842,0.00007688785,0.00007664954,0.0002199644,0.004799274,0.0002736181,0.00005704934,0.0007098209,0.000008887006],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942372,0.0004807383,0.001082885,0.0001236911,0.00002218163,0.00004273534,0.002357838,0.00003689298,0.001615757],"genre_scores_gemma":[0.9967204,0.0001290099,0.00154982,0.00001908839,0.00001782177,0.0000256994,0.001313662,0.000005101778,0.0002193865],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01525312,"threshold_uncertainty_score":0.03032869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.128617173564043,"score_gpt":0.4362511890210319,"score_spread":0.307634015456989,"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."}}