{"id":"W1982845478","doi":"10.5539/jmr.v2n1p103","title":"Modeling and Analysis of an Epidemic Model with Non-monotonic Incidence Rate under Treatment","year":2010,"lang":"en","type":"article","venue":"Journal of Mathematics Research","topic":"Mathematical and Theoretical Epidemiology and Ecology Models","field":"Medicine","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Monotonic function; Mathematics; Epidemic model; Constant (computer programming); Incidence (geometry); Applied mathematics; Statistics; Mathematical economics; Econometrics; Mathematical optimization; Mathematical analysis; Medicine; Computer science; Geometry; Environmental health","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001506387,0.001134637,0.002193182,0.0009089529,0.0008801872,0.001760705,0.003055897,0.003457473,0.005388995],"category_scores_gemma":[0.003435656,0.0008533786,0.001487843,0.0009060157,0.001424335,0.001838121,0.001121072,0.001936203,0.0005249022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002095894,"about_ca_system_score_gemma":0.001632538,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01728859,"about_ca_topic_score_gemma":0.007759108,"domain_scores_codex":[0.9991696,0.0003479192,0.00003189033,0.0001201455,0.00009118787,0.0002391704],"domain_scores_gemma":[0.9982863,0.0008779612,0.0003590152,0.00005197466,0.0002046772,0.0002200268],"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":[0.0001593679,0.0001263989,0.001740426,0.0001267365,0.00008353383,0.0005711548,0.0001930436,0.9527372,0.001722398,0.0383046,0.001116883,0.003118263],"study_design_scores_gemma":[0.00003412021,0.00004203715,0.000270426,0.000008150316,0.00003631143,0.00007378904,0.00002577244,0.9955251,0.00009351894,0.003594175,0.0002816886,0.00001490968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5073317,0.003651048,0.4544035,0.008364221,0.0004047333,0.0003373309,0.001614342,0.0004641693,0.02342907],"genre_scores_gemma":[0.9672014,0.001491471,0.01099679,0.0002683676,0.0001791279,0.0002909838,0.0002571408,0.00004434441,0.01927034],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01728859,"threshold_uncertainty_score":0.03437591,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.123374332355051,"score_gpt":0.4414610668809339,"score_spread":0.3180867345258829,"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."}}