{"id":"W2610656337","doi":"10.1093/cid/cix123","title":"From SARS to Avian Influenza Preparedness in Hong Kong","year":2017,"lang":"en","type":"article","venue":"Clinical Infectious Diseases","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":44,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Preparedness; Medicine; Influenza A virus subtype H5N1; Pandemic; Public health; Infection control; Government (linguistics); Medical emergency; Epidemiology; Emergency management; Environmental health; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty); Immunology; Nursing; Intensive care medicine; Disease; Economic growth; Political science; Pathology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0008497933,0.000187575,0.0001501237,0.000381094,0.0007001941,0.0007933219,0.0002212805,0.0002269942,0.002865035],"category_scores_gemma":[0.001342661,0.0001618786,0.0002397029,0.0005299664,0.0008561832,0.0005775988,0.0008391005,0.0005071611,0.00016793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004035783,"about_ca_system_score_gemma":0.004705004,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3163717,"about_ca_topic_score_gemma":0.2189871,"domain_scores_codex":[0.9995858,0.0001548339,0.00003446334,0.00002926244,0.00002916721,0.0001665213],"domain_scores_gemma":[0.9993665,0.000109903,0.0001479178,0.00002598789,0.0001493261,0.0002004573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004554157,0.0002391852,0.9221131,0.0004161637,0.00009689185,0.00764574,0.01540106,0.0006478795,0.0006124753,0.002865746,0.01061863,0.03888777],"study_design_scores_gemma":[0.00002672596,0.0003147078,0.949448,0.0003700667,0.00004407379,0.001106593,0.03714731,0.0003467345,0.0002235158,0.0004980619,0.01045225,0.0000218868],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9779226,0.004428498,0.00009172469,0.005421921,0.0001603867,0.0000468199,0.0002713942,0.000006187766,0.01165048],"genre_scores_gemma":[0.9945295,0.003205323,0.00005385003,0.0005836806,0.00005624849,0.00001062324,0.0001207706,0.000001294216,0.001438673],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3163717,"threshold_uncertainty_score":0.6290604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1908872651800766,"score_gpt":0.518143740759616,"score_spread":0.3272564755795394,"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."}}