{"id":"W3090569580","doi":"10.1016/j.epidem.2020.100406","title":"Quantifying mechanistic traits of influenza viral dynamics using in vitro data","year":2020,"lang":"en","type":"article","venue":"Epidemics","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Division of Mathematical Sciences; RIKEN; Natural Sciences and Engineering Research Council of Canada; Department for International Development; National Institute for Health and Care Research; Government of Ontario; Wellcome Trust; Medical Research Council; Wellcome","keywords":"Biology; Influenza A virus subtype H5N1; Pandemic; Influenza A virus; Generation time; Adaptation (eye); Reproduction; Basic reproduction number; Viral replication; Strain (injury); In vitro; Virology; Replication (statistics); Virus; Genetics; Coronavirus disease 2019 (COVID-19); Infectious disease (medical specialty)","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":[0.00197435,0.0009150003,0.0008399796,0.0009812546,0.0004397379,0.001296808,0.0007738741,0.001197443,0.001006185],"category_scores_gemma":[0.005550896,0.0004655245,0.001235504,0.001197483,0.0004613067,0.001088006,0.0006434228,0.001407546,0.000566401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009755139,"about_ca_system_score_gemma":0.0003747942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002472945,"about_ca_topic_score_gemma":0.002509244,"domain_scores_codex":[0.9986172,0.0004365617,0.0002033258,0.0002894349,0.0003442199,0.0001092078],"domain_scores_gemma":[0.9946396,0.00280868,0.0008393439,0.0008228678,0.0007288262,0.0001606349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004599792,0.0004299516,0.03304476,0.0007464747,0.0002579809,0.0002203696,0.0004252252,0.08075766,0.8726305,0.001295343,0.0003586429,0.009373032],"study_design_scores_gemma":[0.00002754268,0.001227438,0.06441031,0.00006643236,0.0002485037,0.0004807119,0.0003708891,0.246768,0.6800025,0.002242662,0.003938415,0.0002166697],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9073078,0.001982789,0.07231767,0.0001636311,0.00009474649,0.0002533096,0.01513459,0.0003677807,0.002377628],"genre_scores_gemma":[0.9467264,0.001551976,0.03759019,0.0001295596,0.00003106866,0.0003471376,0.01299576,0.00007519106,0.000552714],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002472945,"threshold_uncertainty_score":0.01044148,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4921865770821297,"score_gpt":0.4763786916530229,"score_spread":0.01580788542910672,"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."}}