{"id":"W4384938027","doi":"10.1016/j.epidem.2023.100708","title":"The effective reproductive number: Modeling and prediction with application to the multi-wave Covid-19 pandemic","year":2023,"lang":"en","type":"article","venue":"Epidemics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Manitoba Health; George & Fay Yee Centre for Healthcare Innovation","funders":"Canadian Institutes of Health Research","keywords":"Pandemic; Coronavirus disease 2019 (COVID-19); Basic reproduction number; Epidemic model; Homogeneous; Infectious disease (medical specialty); Population; Homogeneity (statistics); Disease; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); 2019-20 coronavirus outbreak; Demography; Econometrics; Incidence (geometry); Computer science; Geography; Biology; Medicine; Statistics; Virology; Statistical physics; Mathematics; Environmental health; Physics; Outbreak; Internal medicine","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002299737,0.0006534932,0.0005880579,0.0006693211,0.0004917556,0.000828651,0.001194737,0.001316957,0.0006165651],"category_scores_gemma":[0.00845997,0.0003409368,0.0004646469,0.000609422,0.0006899077,0.001006744,0.0006417019,0.001085487,0.0001048407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125649,"about_ca_system_score_gemma":0.0005653832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03312682,"about_ca_topic_score_gemma":0.01237629,"domain_scores_codex":[0.9997637,0.0001289524,0.000009491201,0.00004253925,0.00002611003,0.00002919422],"domain_scores_gemma":[0.9960536,0.003233177,0.0003170974,0.0001121851,0.0002020696,0.00008185455],"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":[0.0000279922,0.00002672584,0.00520273,0.00001136527,0.00001054268,0.00004786338,0.00004692213,0.9888597,0.0001432368,0.002417132,0.0002480792,0.002957679],"study_design_scores_gemma":[0.00000283855,0.000006940525,0.0005104229,0.000001910586,0.000001902173,0.000005458242,0.000007437375,0.9983894,0.00003630078,0.0009957129,0.00003842245,0.00000331831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9039731,0.0007892367,0.09028185,0.001431649,0.00004251966,0.00006297629,0.0004326853,0.0001581932,0.002827693],"genre_scores_gemma":[0.9895279,0.000254974,0.009187502,0.00003634486,0.00002649749,0.0000393646,0.0001684938,0.00001533768,0.0007436145],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03312682,"threshold_uncertainty_score":0.06586802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2712414176204408,"score_gpt":0.4374250246597246,"score_spread":0.1661836070392838,"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."}}