{"id":"W3197860496","doi":"10.1098/rsos.202255","title":"Optimal shutdown strategies for COVID-19 with economic and mortality costs: British Columbia as a case study","year":2021,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; McGill University; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Shutdown; Economic cost; Variable cost; Coronavirus disease 2019 (COVID-19); Variable (mathematics); Value (mathematics); Economic model; Epidemic model; Economics; Process (computing); Value of life; Cost–benefit analysis; Pareto principle; Operations research; Actuarial science; Computer science; Operations management; Microeconomics; Statistics; Demography; Engineering; Mathematics; Political science; Sociology; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001639824,0.001198025,0.001193998,0.001402139,0.001874613,0.002656094,0.001995999,0.002305098,0.00541932],"category_scores_gemma":[0.007182269,0.0006286315,0.0007560678,0.001346904,0.001276287,0.0009694499,0.001252305,0.002280889,0.0002234564],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02016948,"about_ca_system_score_gemma":0.01346113,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7992757,"about_ca_topic_score_gemma":0.7996104,"domain_scores_codex":[0.999049,0.0003359298,0.00002706214,0.00006999711,0.0000908486,0.0004271595],"domain_scores_gemma":[0.9973071,0.001620044,0.0001863557,0.00007537866,0.000466279,0.000344997],"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":[0.0003440882,0.0003374989,0.00663689,0.0001473192,0.00008698177,0.0007849988,0.0001531175,0.9586666,0.0006576956,0.01793199,0.00401731,0.01023555],"study_design_scores_gemma":[0.0002594255,0.0002822676,0.005691162,0.00007520265,0.00009443327,0.00009223174,0.00137265,0.9768222,0.0004165674,0.01091877,0.003892618,0.00008247086],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9321985,0.001252016,0.01956208,0.003617201,0.0000948477,0.0006630686,0.001528207,0.0001141023,0.04096999],"genre_scores_gemma":[0.9838465,0.0004787564,0.006058903,0.0001484228,0.00001057633,0.0001568348,0.0003375773,0.00002655482,0.008935883],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2007243,"threshold_uncertainty_score":0.4038128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1692976489312676,"score_gpt":0.4490371761390238,"score_spread":0.2797395272077562,"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."}}