{"id":"W4283259101","doi":"10.1016/j.lansea.2022.100031","title":"The global response: How cities and provinces around the globe tackled Covid-19 outbreaks in 2021","year":2022,"lang":"en","type":"article","venue":"The Lancet Regional Health - Southeast Asia","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Pandemic; Contact tracing; Social distance; Transmission (telecommunications); Globe; Coronavirus disease 2019 (COVID-19); Geography; Population; Isolation (microbiology); Outbreak; Enforcement; Limiting; Economic growth; Socioeconomics; Business; Development economics; Environmental health; Political science; Medicine; Economics; Virology; Computer science; Disease; Engineering; Law","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":[0.003013455,0.0008820031,0.0004150247,0.0006237371,0.001356792,0.003492037,0.001849579,0.001351784,0.004535208],"category_scores_gemma":[0.003727647,0.0002580738,0.0009187773,0.001042202,0.001717863,0.001974864,0.003009828,0.001100901,0.0006189729],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007300715,"about_ca_system_score_gemma":0.01364129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2132384,"about_ca_topic_score_gemma":0.2492374,"domain_scores_codex":[0.998328,0.0005875707,0.00003120251,0.000138405,0.0001742498,0.0007405692],"domain_scores_gemma":[0.9986854,0.0001204594,0.0002500038,0.0001061315,0.000455479,0.0003825001],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001281094,0.0007169541,0.5281246,0.00170166,0.0009118887,0.001869221,0.01072726,0.2256517,0.007087558,0.04168003,0.05889944,0.1213486],"study_design_scores_gemma":[0.0003830478,0.002391758,0.4962455,0.001270081,0.0007806392,0.0006204153,0.113723,0.1873257,0.005234505,0.02570127,0.1659129,0.0004112365],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8961826,0.002166166,0.01083924,0.03840662,0.0006296961,0.0006047274,0.002301463,0.0003855828,0.04848389],"genre_scores_gemma":[0.9911971,0.0006594907,0.002673686,0.001626203,0.00003006933,0.00007954767,0.0005355206,0.00003686951,0.003161618],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2132384,"threshold_uncertainty_score":0.4239945,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2310576939849056,"score_gpt":0.4331116111133723,"score_spread":0.2020539171284667,"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."}}