{"id":"W3081661859","doi":"10.1080/15398285.2020.1794193","title":"Influenza Pandemic: A Webliography","year":2020,"lang":"fr","type":"article","venue":"Journal of Consumer Health on the Internet","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Pandemic; Outbreak; Human mortality from H5N1; Isolation (microbiology); Influenza pandemic; China; Coronavirus disease 2019 (COVID-19); Coronavirus; Influenza A virus subtype H5N1; Geography; Virology; Disease; Infectious disease (medical specialty); Medicine; Virus; Biology; 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":[0.0005506922,0.001120846,0.0006289089,0.002554929,0.001398218,0.004481502,0.0006967242,0.002528966,0.1312953],"category_scores_gemma":[0.003051174,0.0003195964,0.0004918203,0.002219348,0.0008019399,0.005500446,0.002732891,0.002616595,0.0981785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006970754,"about_ca_system_score_gemma":0.001203244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001724066,"about_ca_topic_score_gemma":0.003921177,"domain_scores_codex":[0.9994991,0.0001062433,0.00002958551,0.00004569559,0.0002669398,0.0000525379],"domain_scores_gemma":[0.9979954,0.0005552863,0.0001235035,0.0001059585,0.000617607,0.000602326],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001766459,0.00003299226,0.0002426701,0.0001719276,0.000002655816,0.00008086469,0.000105554,0.00002995028,0.0004842647,0.0009807531,0.9307613,0.06708942],"study_design_scores_gemma":[0.000002146432,0.00001854015,0.0004506397,0.0001674931,0.000001693613,0.0001444028,0.0001049859,0.00004928229,0.00006062414,0.0003822862,0.9986125,0.000005400136],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006255396,0.04608734,0.01395849,0.1052504,0.1226459,0.0008948125,0.008645429,0.008922281,0.68734],"genre_scores_gemma":[0.009241926,0.02653558,0.01149946,0.05566042,0.03755891,0.0002611903,0.005180218,0.002361143,0.8517011],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.1312953,"threshold_uncertainty_score":0.4392264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04261524690534653,"score_gpt":0.3253403259615426,"score_spread":0.2827250790561961,"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."}}