{"id":"W2962841257","doi":"10.3934/dcdsb.2015.20.1685","title":"Modeling of contact tracing in epidemic populations structured by disease age","year":2015,"lang":"en","type":"article","venue":"Discrete and Continuous Dynamical Systems - B","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"","keywords":"Contact tracing; Public health; Smallpox; Preparedness; Psychological intervention; Outbreak; Uniqueness; Population; Public health interventions; Quarantine; Ordinary differential equation; Epidemic model; Medicine; Infectious disease (medical specialty); Disease; Environmental health; Computer science; Differential equation; Mathematics; Virology; Psychology; Coronavirus disease 2019 (COVID-19); Vaccination; Political science; Social psychology; Pathology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001539768,0.0007018567,0.001045231,0.001072151,0.0005821932,0.001355313,0.002234475,0.002697894,0.002994561],"category_scores_gemma":[0.006416148,0.0006733147,0.001010799,0.0008647186,0.001359419,0.001878394,0.001546023,0.001122544,0.0004388527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201899,"about_ca_system_score_gemma":0.0009127546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0124194,"about_ca_topic_score_gemma":0.005621803,"domain_scores_codex":[0.9993653,0.0002944609,0.00003413001,0.0001354052,0.00006500301,0.0001057251],"domain_scores_gemma":[0.9971458,0.001707124,0.0005298865,0.0001264059,0.0002348271,0.0002558493],"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":[0.00005287896,0.00005655976,0.004517938,0.00002854639,0.00004557456,0.000259588,0.0002471013,0.9615711,0.0006128094,0.0295889,0.0005250582,0.002493975],"study_design_scores_gemma":[0.00001480382,0.00001887677,0.0003527343,0.000004663314,0.000009473686,0.00002670771,0.00003198574,0.9940661,0.00003741081,0.005207875,0.0002222985,0.00000711544],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4847608,0.000636433,0.4978423,0.002838979,0.0001138695,0.0001642316,0.0009487035,0.000288469,0.01240628],"genre_scores_gemma":[0.9732785,0.0004326168,0.01534128,0.0001947593,0.00006464489,0.000192679,0.0002620004,0.00003847671,0.01019515],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0124194,"threshold_uncertainty_score":0.0246942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1512145726057616,"score_gpt":0.3815650072657028,"score_spread":0.2303504346599412,"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."}}