{"id":"W3024566327","doi":"10.1016/j.mbs.2020.108378","title":"Modeling the impact of mass influenza vaccination and public health interventions on COVID-19 epidemics with limited detection capability","year":2020,"lang":"en","type":"article","venue":"Mathematical Biosciences","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":142,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"Canadian Institutes of Health Research; National Natural Science Foundation of China","keywords":"Public health; Psychological intervention; Vaccination; Pandemic; Outbreak; Medicine; Environmental health; Transmission (telecommunications); Health care; Intensive care medicine; Coronavirus disease 2019 (COVID-19); Immunology; Virology; Infectious disease (medical specialty); Economic growth; Disease; Nursing; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001699879,0.0001078137,0.0002953674,0.000109248,0.000273927,0.00004334786,0.0001200473,0.00003532782,0.00003065878],"category_scores_gemma":[0.01086978,0.00005185054,0.00009829439,0.00063923,0.0003275252,0.0001309971,0.00005898852,0.0001880532,0.000003985889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001912266,"about_ca_system_score_gemma":0.0002841412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001765607,"about_ca_topic_score_gemma":0.00003344423,"domain_scores_codex":[0.9985011,0.0001774174,0.0003959457,0.000234179,0.0004367774,0.0002545342],"domain_scores_gemma":[0.9986961,0.0004945339,0.0001208996,0.0001702492,0.000164089,0.0003541299],"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":[0.00709602,0.008698462,0.40049,0.04756892,0.002632292,0.00003127963,0.146206,0.08860396,0.0509157,0.07024519,0.0009333476,0.1765789],"study_design_scores_gemma":[0.001058998,0.00458896,0.01696374,0.0002376201,0.00003718138,0.00001345634,0.004790388,0.9642066,0.0005014995,0.007430478,0.00002983797,0.0001412667],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.889949,0.0001655712,0.08947606,0.01951383,0.000007898868,0.0006790491,0.00001296133,0.00004589255,0.0001497873],"genre_scores_gemma":[0.9971225,0.00003434252,0.001186493,0.001608631,0.00001483211,0.00002560991,8.532036e-7,0.000004790094,0.000001948051],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8756026,"threshold_uncertainty_score":0.9974621,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3527767618055422,"score_gpt":0.4826575940288882,"score_spread":0.129880832223346,"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."}}