{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","sts"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.05576894,0.0005694282,0.003891173,0.001205737,0.003785543,0.00102096,0.001666181,0.000164169,0.00001297081],"category_scores_gemma":[0.0239602,0.0003787437,0.0001643153,0.005789608,0.002376374,0.0004706131,0.002544905,0.0008490889,0.00001079375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003698405,"about_ca_system_score_gemma":0.002474214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003251695,"about_ca_topic_score_gemma":0.00001960491,"domain_scores_codex":[0.9878729,0.002646194,0.00202388,0.001884802,0.003974416,0.001597825],"domain_scores_gemma":[0.9885551,0.007148192,0.0008266622,0.001097268,0.000847873,0.001524852],"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":[0.00000422948,0.00007215255,0.0000153482,0.9918169,0.00001548288,0.00004393579,0.000215833,0.001517812,0.000005525379,0.004089469,0.0000463631,0.002156906],"study_design_scores_gemma":[0.0002278446,0.0009232811,7.116133e-7,0.8038169,0.001194513,0.000420551,0.002320316,0.09520677,2.067382e-7,0.001058451,0.09336049,0.001470007],"study_design_candidate":"systematic_review","study_design_consensus":"systematic_review","genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003069126,0.9810739,0.004992426,0.00004031419,0.0002449725,0.01314647,0.00006584336,0.00008865958,0.00004055963],"genre_scores_gemma":[0.005152596,0.9919891,0.0004310651,0.00004328501,0.0000772688,0.002065314,0.000003853715,0.0000396642,0.0001977989],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.1880001,"threshold_uncertainty_score":0.9998664,"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."}}