{"id":"W4321639696","doi":"10.1093/ageing/afab219.36","title":"36 A YEAR WITHOUT THE FLU: MODELLING THE EFFECTS ON CARDIOVASCULAR MORTALITY FROM INFLUENZA IN IRELAND","year":2021,"lang":"en","type":"article","venue":"Age and Ageing","topic":"Cardiovascular Health and Risk Factors","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Demography; Mortality rate; Myocardial infarction; Population; Pandemic; Stroke (engine); Quarter (Canadian coin); Disease; Internal medicine; Coronavirus disease 2019 (COVID-19); Environmental health; Infectious disease (medical specialty)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003394607,0.00150441,0.001419381,0.001257229,0.0006125026,0.001898705,0.003254475,0.003506373,0.005057359],"category_scores_gemma":[0.008328293,0.001208702,0.003390645,0.0008928189,0.001021418,0.0009291556,0.001886834,0.00236951,0.0009495559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004251812,"about_ca_system_score_gemma":0.0032406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1965211,"about_ca_topic_score_gemma":0.07836843,"domain_scores_codex":[0.9987527,0.0005697685,0.00005102627,0.0002258451,0.00004593471,0.0003546783],"domain_scores_gemma":[0.9951567,0.003306199,0.0004221229,0.0001489152,0.0003778065,0.0005882501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005572612,0.0003752073,0.04691394,0.000111338,0.0002637079,0.0003171586,0.0001135133,0.9461934,0.0001903486,0.001055203,0.00180439,0.002104658],"study_design_scores_gemma":[0.0001202903,0.0002087763,0.00992577,0.00002823013,0.00007755512,0.00004867432,0.0001801193,0.9880235,0.00006037938,0.0006846873,0.0005964229,0.00004560362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843937,0.0004431501,0.004177815,0.001003735,0.0001319881,0.0001516205,0.006139858,0.0001750647,0.003383041],"genre_scores_gemma":[0.991981,0.0001764896,0.001725953,0.0001402088,0.00004834869,0.0001883731,0.002588788,0.00003796004,0.003112953],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1965211,"threshold_uncertainty_score":0.3907545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02529000394067915,"score_gpt":0.2753025022897224,"score_spread":0.2500124983490433,"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."}}