{"id":"W4411140207","doi":"10.1016/j.eswa.2025.128482","title":"Leveraging social media and google trends to identify waves of avian influenza outbreaks in USA and Canada","year":2025,"lang":"en","type":"article","venue":"Expert Systems with Applications","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Food Inspection Agency; University of Guelph","funders":"Ontario Ministry of Agriculture, Food and Rural Affairs; University of Guelph","keywords":"Outbreak; Social media; Influenza A virus subtype H5N1; Computer science; Data science; Virology; World Wide Web; Biology; Virus","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007032828,0.0003568745,0.0002575665,0.004430773,0.0006751611,0.001707683,0.0006808985,0.0003760445,0.0008564415],"category_scores_gemma":[0.003890548,0.0001857576,0.0004686471,0.004954481,0.000228376,0.0006221125,0.000651692,0.0004579208,0.0003311883],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005898468,"about_ca_system_score_gemma":0.009231582,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9772309,"about_ca_topic_score_gemma":0.9879658,"domain_scores_codex":[0.9994811,0.00004201033,0.00003951491,0.00008922198,0.0002377144,0.0001104052],"domain_scores_gemma":[0.9967776,0.0004982618,0.0002938579,0.0001134052,0.002022526,0.0002943319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001935201,0.0001079318,0.8965034,0.0002046269,0.0003529242,0.0003449979,0.0008677114,0.006086367,0.00157555,0.0006684404,0.02699512,0.06609938],"study_design_scores_gemma":[0.00001862941,0.00004314446,0.9052757,0.0001122732,0.0002004419,0.0001112577,0.003070718,0.06196559,0.001540975,0.0004813784,0.02711592,0.00006399035],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.901149,0.001793177,0.002680622,0.001911487,0.0001736775,0.0001462709,0.07754442,0.0005074624,0.01409387],"genre_scores_gemma":[0.9580295,0.001004134,0.004347506,0.0002451547,0.00008102915,0.0000363534,0.03214638,0.00004818965,0.0040619],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02276909,"threshold_uncertainty_score":0.04580629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01766921158636678,"score_gpt":0.3135720727454285,"score_spread":0.2959028611590617,"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."}}