{"id":"W2899516655","doi":"10.1080/17513758.2018.1537449","title":"Demographic population cycles and ℛ<sub>0</sub>in discrete-time epidemic models","year":2018,"lang":"en","type":"article","venue":"Journal of Biological Dynamics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Office of the Director; Natural Sciences and Engineering Research Council of Canada; University of Arizona","keywords":"Discrete time and continuous time; Epidemic model; Population; Geography; Demography; Statistics; Econometrics; Mathematics; Sociology","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":[0.0006408432,0.0003710432,0.0003511501,0.0004804035,0.0004171909,0.0007964293,0.0005383822,0.0005498436,0.001566628],"category_scores_gemma":[0.003298918,0.0002211385,0.0004239593,0.0002954277,0.0006251652,0.001023265,0.0006128802,0.0005325779,0.0001474011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007786049,"about_ca_system_score_gemma":0.0005184327,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005503613,"about_ca_topic_score_gemma":0.003227812,"domain_scores_codex":[0.999828,0.00008265908,0.000009693079,0.00002290197,0.00002953975,0.0000272719],"domain_scores_gemma":[0.9990471,0.0004815493,0.0002595983,0.00004668326,0.00008273801,0.00008223297],"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":[0.000059079,0.00008879311,0.009493344,0.00008237598,0.00005760926,0.0004951948,0.000570751,0.6463535,0.002996631,0.3265735,0.002013976,0.01121528],"study_design_scores_gemma":[0.000008547606,0.00001305429,0.0006617705,0.000006844844,0.00001128205,0.00004423768,0.0000360489,0.9618196,0.0001788296,0.03656438,0.0006460498,0.000009292568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7596099,0.001138691,0.2200335,0.001858978,0.00009674873,0.00006356504,0.0001738787,0.0001673466,0.01685745],"genre_scores_gemma":[0.9917865,0.0003781677,0.0051325,0.00008059706,0.00002956975,0.00003669683,0.00004258641,0.00002499156,0.002488442],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005503613,"threshold_uncertainty_score":0.01094317,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1288436640760925,"score_gpt":0.376290939921165,"score_spread":0.2474472758450724,"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."}}