{"id":"W3017151589","doi":"10.12927/hcq.2020.26279","title":"Sustaining Social Distancing and Mass Quarantine in the COVID-19 Era: Lessons Learned","year":2020,"lang":"en","type":"article","venue":"Healthcare Quarterly","topic":"Healthcare Systems and Reforms","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Impact","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Quarantine; Pandemic; Social distance; 2019-20 coronavirus outbreak; Mainland China; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); China; Political science; Development economics; Economic growth; Virology; History; Medicine; Economics; Law; Outbreak","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.01394541,0.0006353538,0.0006973157,0.0009951873,0.003812342,0.0086495,0.002857031,0.005232534,0.0171542],"category_scores_gemma":[0.02799143,0.0002246099,0.0006632073,0.001020807,0.009048207,0.01007886,0.008675416,0.007866458,0.001707016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007576273,"about_ca_system_score_gemma":0.03363091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01401975,"about_ca_topic_score_gemma":0.0284383,"domain_scores_codex":[0.9933543,0.003217594,0.0001476742,0.0003840176,0.0006913588,0.002205063],"domain_scores_gemma":[0.9669356,0.01418273,0.001466668,0.001107619,0.003823482,0.01248401],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003314089,0.001088404,0.01375206,0.002153586,0.0001963587,0.001643856,0.01524814,0.002884518,0.0004371002,0.3852737,0.2110783,0.3659126],"study_design_scores_gemma":[0.0002017431,0.0006521118,0.01856132,0.007181403,0.00006546423,0.0004114961,0.05711639,0.002293999,0.0007428591,0.5289754,0.3836583,0.0001394794],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02512731,0.01735124,0.003746831,0.9097878,0.00276546,0.00009293645,0.0001848206,0.00007697842,0.04086655],"genre_scores_gemma":[0.8105149,0.04269697,0.007240058,0.1231263,0.004644833,0.0003120371,0.0002552913,0.0001185797,0.01109104],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0171542,"threshold_uncertainty_score":0.07375127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1225861496589641,"score_gpt":0.3384492805534804,"score_spread":0.2158631308945163,"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."}}