{"id":"W2167286483","doi":"10.5210/ojphi.v5i1.4470","title":"Influenza Forecasting with Google Flu Trends","year":2013,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Civil, Mechanical and Manufacturing Innovation; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Homeland Security; National Science Foundation","keywords":"Computer science; Warning system; Selection (genetic algorithm); Seasonal influenza; Model selection; Coronavirus disease 2019 (COVID-19); Data mining; Data science; Medicine; Machine learning; Infectious disease (medical specialty); Telecommunications; Disease","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0009421522,0.0006325783,0.000431564,0.001251304,0.000172503,0.0006151347,0.0005495347,0.0004683379,0.001319686],"category_scores_gemma":[0.004706438,0.0002842606,0.0005770381,0.001110473,0.0001320976,0.0009857683,0.0004072453,0.0004352238,0.0004349445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000512007,"about_ca_system_score_gemma":0.0006277998,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0454716,"about_ca_topic_score_gemma":0.0300895,"domain_scores_codex":[0.9996951,0.0001002371,0.0000275906,0.000060193,0.00008154386,0.00003533034],"domain_scores_gemma":[0.9989368,0.0005598615,0.000109549,0.00009951465,0.0002505509,0.0000436473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000288261,0.00009168444,0.05300966,0.0001084545,0.0001076869,0.0001521119,0.00007475234,0.8917009,0.0009272659,0.003632069,0.003599184,0.04630793],"study_design_scores_gemma":[0.000009532831,0.00004276056,0.003536606,0.000006916247,0.00001584041,0.00002823932,0.00001774467,0.9940509,0.0004953171,0.000803953,0.0009841478,0.000007904155],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8583023,0.000514036,0.1161606,0.001228873,0.0002106978,0.0002039888,0.0104005,0.003651968,0.009327126],"genre_scores_gemma":[0.9655098,0.000175287,0.02872115,0.000037461,0.00003837402,0.00005432302,0.004488305,0.00004258889,0.0009327689],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0454716,"threshold_uncertainty_score":0.09041387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1193108027593693,"score_gpt":0.3546440358282462,"score_spread":0.2353332330688769,"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."}}