{"id":"W2760560537","doi":"10.2196/iproc.8686","title":"Detecting Influenza Epidemics Using Self-reported Data Through Mobile App (FeverCoach)","year":2017,"lang":"en","type":"article","venue":"Iproceedings","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Public health surveillance; Public health; The Internet; Internet privacy; Health records; Mobile apps; Influenza-like illness; Lag time; Business; Environmental health; Medicine; Medical emergency; Computer science; Health care; Virology; World Wide Web; Biology; Political science; Nursing","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":[0.0006896773,0.0009430103,0.0006319712,0.001665854,0.0002252831,0.0006133994,0.0005033682,0.000547401,0.001559539],"category_scores_gemma":[0.003192393,0.0002283329,0.0005199914,0.0005551245,0.0001071859,0.0007198368,0.0005724012,0.0004015348,0.000978123],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001790855,"about_ca_system_score_gemma":0.0003267767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003889701,"about_ca_topic_score_gemma":0.006435595,"domain_scores_codex":[0.999566,0.0001000327,0.00005917015,0.000149326,0.00008478934,0.00004052377],"domain_scores_gemma":[0.9984634,0.0007294836,0.0002722522,0.0001164114,0.0003164986,0.0001020115],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001653113,0.001140172,0.6054904,0.002017628,0.0005317798,0.001008326,0.0009874747,0.005822522,0.01144375,0.0005610622,0.02572094,0.3436229],"study_design_scores_gemma":[0.0001819984,0.002721597,0.6600994,0.0006268058,0.0006934106,0.001999585,0.001160381,0.2930052,0.0148966,0.001701518,0.02262124,0.0002923275],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9209692,0.001942564,0.02774807,0.0007599822,0.0003673828,0.001634059,0.02824703,0.01043934,0.007892317],"genre_scores_gemma":[0.9352694,0.0006892692,0.04789499,0.0003751513,0.0001362351,0.0008662188,0.01217692,0.00006556755,0.002526344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003889701,"threshold_uncertainty_score":0.00773412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1611207812623647,"score_gpt":0.4094856190534962,"score_spread":0.2483648377911314,"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."}}