{"id":"W4399813071","doi":"10.1098/rsos.240186","title":"Is SARS-CoV-2 elimination or mitigation best? Regional and disease characteristics determine the recommended strategy","year":2024,"lang":"en","type":"article","venue":"Royal Society Open Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada; Azrieli Foundation; Public Health Agency; Public Health Agency of Canada","keywords":"Mainland China; Business; China; Psychological intervention; Economic cost; Pandemic; Economic impact analysis; Environmental planning; Coronavirus disease 2019 (COVID-19); Disease; Risk analysis (engineering); Geography; Economics; Medicine; Infectious disease (medical specialty)","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":[0.03223057,0.001098283,0.002460203,0.003155671,0.001306497,0.00658322,0.002853027,0.002921819,0.01007938],"category_scores_gemma":[0.08830744,0.0005569774,0.002279145,0.002354611,0.00172246,0.00446953,0.002462179,0.002453237,0.002742448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005871865,"about_ca_system_score_gemma":0.01517283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03501054,"about_ca_topic_score_gemma":0.07258263,"domain_scores_codex":[0.9810332,0.01363365,0.001732982,0.0009821746,0.001604089,0.001013936],"domain_scores_gemma":[0.960809,0.02108888,0.005178454,0.001410975,0.009351263,0.002161448],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001815076,0.0004997612,0.1058954,0.01677402,0.001608874,0.0009348225,0.003937713,0.01289058,0.002363988,0.0446306,0.1077153,0.7009339],"study_design_scores_gemma":[0.001439495,0.002591964,0.2027094,0.05680354,0.004976251,0.001820737,0.03066253,0.02235172,0.007324594,0.1292525,0.5392619,0.0008053308],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.123561,0.1289481,0.1189195,0.4798866,0.003796389,0.004202857,0.01345976,0.001208527,0.1260172],"genre_scores_gemma":[0.6717936,0.05192591,0.2365197,0.02583404,0.001348992,0.002932213,0.002893691,0.000553382,0.006198333],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03501054,"threshold_uncertainty_score":0.1704536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3129834191775346,"score_gpt":0.4668519474384372,"score_spread":0.1538685282609025,"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."}}