{"id":"W2765572340","doi":"10.2196/publichealth.7344","title":"Combining Participatory Influenza Surveillance with Modeling and Forecasting: Three Alternative Approaches","year":2017,"lang":"en","type":"article","venue":"JMIR Public Health and Surveillance","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"H2020 Future and Emerging Technologies; National Institute of General Medical Sciences; Horizon 2020 Framework Programme; European Commission; Skoll Foundation; Defense Threat Reduction Agency; National Institutes of Health; National Science Foundation","keywords":"Outbreak; Psychological intervention; Environmental health; Disease surveillance; Citizen journalism; Medicine; Public health; Medical emergency; Computer science; Virology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01482006,0.002516558,0.001557495,0.002360545,0.001041014,0.004651419,0.003588584,0.002793634,0.002203819],"category_scores_gemma":[0.04072943,0.001242509,0.002997004,0.002782737,0.001933396,0.004657625,0.00773854,0.00213354,0.0002822888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002215657,"about_ca_system_score_gemma":0.002665515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01045539,"about_ca_topic_score_gemma":0.008379261,"domain_scores_codex":[0.9820883,0.01286151,0.0006366738,0.001704481,0.002227746,0.0004812705],"domain_scores_gemma":[0.9684672,0.02252109,0.001907772,0.005014356,0.001637196,0.0004523942],"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":[0.0006546026,0.0005698242,0.02595573,0.001015498,0.001572696,0.0005088457,0.003649971,0.5957149,0.003560568,0.1499023,0.001540317,0.2153548],"study_design_scores_gemma":[0.00009382218,0.0002267698,0.001887908,0.0001666255,0.0001863986,0.00009670547,0.0004649405,0.8611506,0.001363346,0.1294987,0.004735515,0.000128641],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02847287,0.0006670179,0.9614585,0.002558758,0.000129632,0.0002938849,0.0002264048,0.000273442,0.005919643],"genre_scores_gemma":[0.4537917,0.000769283,0.5422066,0.0003789157,0.0002109008,0.0008026892,0.0002578844,0.00007207758,0.001509876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01482006,"threshold_uncertainty_score":0.07837689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2659580252915658,"score_gpt":0.3601577780503601,"score_spread":0.09419975275879428,"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."}}