{"id":"W2910006651","doi":"10.1016/j.epidem.2018.12.002","title":"A practical generation-interval-based approach to inferring the strength of epidemics from their speed","year":2019,"lang":"en","type":"article","venue":"Epidemics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; McMaster University","funders":"Army Research Office; Canadian Institutes of Health Research","keywords":"Generation time; Interval (graph theory); Statistics; Mathematics; Rabies; Exponential growth; Applied mathematics; Basic reproduction number; Econometrics; Biology; Combinatorics; Virology; Mathematical analysis; Demography; Population","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":[0.004001336,0.0005899151,0.0007530808,0.001941906,0.0004792207,0.001147512,0.001797514,0.001053453,0.003001151],"category_scores_gemma":[0.02564894,0.0005374976,0.0007821319,0.001572381,0.0007812208,0.001474714,0.001132467,0.00179116,0.0004919419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007723902,"about_ca_system_score_gemma":0.000621508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004632567,"about_ca_topic_score_gemma":0.003565752,"domain_scores_codex":[0.9986564,0.0008095988,0.00005165459,0.0002541483,0.0001684574,0.00005972133],"domain_scores_gemma":[0.9910913,0.007032139,0.0006456849,0.0007180564,0.0004038535,0.000109006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001172462,0.00006824891,0.01050066,0.0001173662,0.0001198734,0.0002440478,0.0003646153,0.7483293,0.001689742,0.1480252,0.001727875,0.08869578],"study_design_scores_gemma":[0.00000944489,0.00002434414,0.001295331,0.00001742979,0.00001451101,0.0001238829,0.00002676564,0.9471958,0.0002582136,0.04995903,0.001060099,0.00001521309],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01263055,0.0001717642,0.9851828,0.0001934878,0.00001943108,0.00003635445,0.0001276514,0.0001903844,0.001447538],"genre_scores_gemma":[0.4389223,0.0005392895,0.5566147,0.0001788617,0.0001003437,0.0001756987,0.0007051258,0.00009141663,0.002672276],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004632567,"threshold_uncertainty_score":0.02116132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3963448800162717,"score_gpt":0.4381429652915548,"score_spread":0.04179808527528311,"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."}}