{"id":"W4292542388","doi":"10.1002/sres.2897","title":"Using simulation modelling and systems science to help contain COVID‐19: A systematic review","year":2022,"lang":"en","type":"review","venue":"Systems Research and Behavioral Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Computer science; Pandemic; Intervention (counseling); Management science; Discrete event simulation; Psychological intervention; Risk analysis (engineering); Macro; Operations research; Data science; Systems engineering; Simulation; Engineering; Psychology; Medicine","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":[0.009981209,0.001373668,0.003997061,0.01058254,0.0005180081,0.00272845,0.001462799,0.002119578,0.004717398],"category_scores_gemma":[0.05012493,0.0008627772,0.005577973,0.009363658,0.000750358,0.002771905,0.001441896,0.001537068,0.0005472711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00284059,"about_ca_system_score_gemma":0.01450379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006609194,"about_ca_topic_score_gemma":0.01439688,"domain_scores_codex":[0.9932393,0.003156638,0.001889645,0.000367788,0.001208765,0.0001379249],"domain_scores_gemma":[0.9573495,0.03635843,0.002715026,0.0007224522,0.002601481,0.0002531292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"systematic_review","study_design_gemma":"systematic_review","study_design_scores_codex":[0.0001105146,0.00003934826,0.0005024595,0.7257906,0.004092711,0.0001091803,0.0002358991,0.0009176886,0.0001770107,0.00353799,0.0048641,0.2596225],"study_design_scores_gemma":[0.0001062484,0.0002010757,0.001575399,0.8478392,0.01652115,0.0003570278,0.000342361,0.000544093,0.0002515663,0.003330331,0.128873,0.00005861495],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001754055,0.9984674,0.0004761381,0.0003230862,0.0001155224,0.00009728462,0.00007546067,0.000007458014,0.0002622317],"genre_scores_gemma":[0.003412537,0.9948564,0.001054474,0.000291881,0.00006197329,0.0001581923,0.00007615709,0.000004633715,0.00008379773],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01058254,"threshold_uncertainty_score":0.05278635,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.9079918223279512,"score_gpt":0.6714071788160251,"score_spread":0.2365846435119261,"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."}}