{"id":"W2982655119","doi":"10.1007/s13524-019-00824-z","title":"Correction to: Determinants of Influenza Mortality Trends: Age-Period-Cohort Analysis of Influenza Mortality in the United States, 1959–2016","year":2019,"lang":"en","type":"erratum","venue":"Demography","topic":"Influenza Virus Research Studies","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University Medical Centre; McMaster University; Statistics Canada; University of Guelph; Université de Montréal","funders":"","keywords":"Demography; Lexis; Medicine; Influenza pandemic; Mortality rate; Geography; Virology; Coronavirus disease 2019 (COVID-19); Disease; Infectious disease (medical specialty); Internal medicine; Sociology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002682358,0.0008764338,0.00334338,0.009450045,0.0001574758,0.00006024914,0.0009523423,0.000701668,0.0001273899],"category_scores_gemma":[0.001260457,0.0006463048,0.001639895,0.01769508,0.0008703885,0.0001717655,0.0003153754,0.001892858,0.00001484668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002123115,"about_ca_system_score_gemma":0.000455139,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02977599,"about_ca_topic_score_gemma":0.01147858,"domain_scores_codex":[0.9920397,0.0008128054,0.002463569,0.001121471,0.002536095,0.00102631],"domain_scores_gemma":[0.9942254,0.0005392466,0.001232689,0.002610532,0.001123567,0.0002685632],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003734284,0.000424768,0.8446479,0.0007270463,0.007663823,0.00009721123,0.001902669,0.0004813301,0.00003783369,0.000004937215,0.1424707,0.001168341],"study_design_scores_gemma":[0.0009835598,0.0004717241,0.8828121,0.000913279,0.005916988,0.00000384094,0.000778801,0.001394797,0.00005566211,0.00001151113,0.1061773,0.000480372],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9843473,0.002255003,0.00001103683,0.00003279706,0.003801493,0.001716664,0.001517248,0.00007024015,0.006248165],"genre_scores_gemma":[0.9591957,0.007357135,0.0002429415,0.008441631,0.001020466,0.001349932,0.008937784,0.000414903,0.01303947],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03816423,"threshold_uncertainty_score":0.9995988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07451904512354394,"score_gpt":0.4037517328526556,"score_spread":0.3292326877291117,"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."}}