{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007889096,0.0002252295,0.0008992926,0.00005721462,0.0000614765,0.00002766273,0.0001427838,0.0001296683,0.00000253082],"category_scores_gemma":[0.003132352,0.0001686672,0.0001087144,0.0001228669,0.00006690375,0.0000923482,0.0000974753,0.0001970416,5.880342e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001132558,"about_ca_system_score_gemma":0.00002034993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003359232,"about_ca_topic_score_gemma":0.0005231343,"domain_scores_codex":[0.9978237,0.0003406426,0.0009139462,0.0003607951,0.0002258922,0.0003350856],"domain_scores_gemma":[0.9985931,0.0006347726,0.0002014896,0.0002443343,0.00006398636,0.0002623392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007036603,0.0003616039,0.6102977,0.001804244,0.000309023,0.0001595259,0.003279696,0.041714,0.002252688,0.33559,0.001844741,0.001683029],"study_design_scores_gemma":[0.0009740514,0.0000757421,0.01122795,0.000357024,0.00008891732,0.000003110963,0.0009716716,0.8879755,0.000001125194,0.0979691,0.00004389179,0.0003119788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9321428,0.001833583,0.06472802,0.0002606258,0.0001130415,0.0005387182,0.0001228366,0.00006584211,0.0001945328],"genre_scores_gemma":[0.9993268,0.00001624507,0.0003815877,0.00005044539,0.00004016608,0.00004645989,0.00004414011,0.00001939116,0.00007473536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8462614,"threshold_uncertainty_score":0.6878048,"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."}}