{"id":"W2094282308","doi":"10.1016/j.apm.2009.12.005","title":"Global analysis of an SEIR model with varying population size and vaccination","year":2009,"lang":"en","type":"article","venue":"Applied Mathematical Modelling","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":149,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Mitacs; National Science Council; University of Manitoba","keywords":"Population; Population size; Vaccination; Stability (learning theory); Mathematics; Statistics; Econometrics; Biology; Medicine; Computer science; Virology; Environmental health","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004824272,0.0001608313,0.0007448226,0.00006073065,0.00007009949,0.000007390462,0.00005347007,0.000179588,0.00008505976],"category_scores_gemma":[0.00007846951,0.0001113638,0.00007794905,0.0003140975,0.00006405474,0.00007433273,0.00001541574,0.0001154798,0.000001841188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002237932,"about_ca_system_score_gemma":0.00001505063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000246839,"about_ca_topic_score_gemma":7.509457e-7,"domain_scores_codex":[0.9988285,0.0000263139,0.00046189,0.0002943514,0.0001634144,0.000225497],"domain_scores_gemma":[0.999049,0.0003922965,0.0001107535,0.0002295992,0.00005202528,0.0001662976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001903131,0.0002808993,0.00008602866,0.00008534315,0.0001786593,0.000001382303,0.0001000243,0.2874212,0.00004250623,0.710534,3.568979e-7,0.001079305],"study_design_scores_gemma":[0.0002649159,0.0000899545,0.0009784185,0.00001797227,0.0009481607,0.000006457309,0.000008887059,0.5289035,0.0000255311,0.4686942,2.954654e-8,0.0000620049],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4074338,0.000008936644,0.5834821,0.0001828994,0.000001626787,0.0001737407,0.000001930572,0.00003430223,0.008680644],"genre_scores_gemma":[0.8701765,0.000005306648,0.1294359,0.0003237639,0.00001015678,0.00001073741,0.00001709279,0.000006488433,0.00001412659],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4627427,"threshold_uncertainty_score":0.4541283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02500525316300741,"score_gpt":0.2923579024252977,"score_spread":0.2673526492622904,"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."}}