{"id":"W2973391458","doi":"10.1016/j.aml.2019.106052","title":"Threshold dynamics of a vector-borne disease model with spatial structure and vector-bias","year":2019,"lang":"en","type":"article","venue":"Applied Mathematics Letters","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Science Foundation of Heilongjiang Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Mathematics; Bounded function; Eigenvalues and eigenvectors; Dynamics (music); Vector (molecular biology); Domain (mathematical analysis); Applied mathematics; Principal (computer security); Basic reproduction number; Mathematical analysis; Computer science","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":[0.000208695,0.00022985,0.0006830131,0.00005248242,0.00003857158,0.000006301733,0.00009603746,0.0001401007,0.0002220566],"category_scores_gemma":[0.00006492087,0.0001507693,0.00006704035,0.00006815592,0.0003816946,0.00002758083,0.00006275033,0.000268067,0.00001686934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000242122,"about_ca_system_score_gemma":0.00003483244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003083113,"about_ca_topic_score_gemma":0.000003858771,"domain_scores_codex":[0.9988506,0.0000115856,0.0003709017,0.0002934452,0.0001872464,0.0002861983],"domain_scores_gemma":[0.9988907,0.0003253205,0.0001498874,0.0004025224,0.0000295563,0.0002020325],"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":[0.000360355,0.0001586814,0.001039421,0.00127402,0.0001263199,0.000009339212,0.0002219489,0.001062002,0.003903128,0.9917375,0.00006233036,0.00004496713],"study_design_scores_gemma":[0.001702333,0.0001735697,0.004240497,0.0002185561,0.0004185562,0.00003275019,0.00006091993,0.725071,0.0007334382,0.2670637,0.000002554531,0.0002821495],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8738945,0.00001203906,0.1169174,0.005668378,0.0000249269,0.0006113502,0.00002602519,0.00004002847,0.002805386],"genre_scores_gemma":[0.9819455,0.000004484545,0.01625079,0.001617855,0.00002700188,0.00002238045,0.00003035512,0.00002997938,0.00007162986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7246737,"threshold_uncertainty_score":0.6148192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01356338019739332,"score_gpt":0.2327493282287977,"score_spread":0.2191859480314044,"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."}}