{"id":"W3179103999","doi":"10.1016/j.jue.2021.103373","title":"JUE Insight: The geography of pandemic containment","year":2021,"lang":"en","type":"article","venue":"Journal of Urban Economics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Bank of Canada","funders":"","keywords":"Toll; Welfare; Pandemic; Containment (computer programming); Economics; Coronavirus disease 2019 (COVID-19); State (computer science); Public economics; Market economy; Computer science","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":[0.001164648,0.0004279514,0.0008393155,0.002117921,0.001658059,0.006479021,0.000996004,0.002529914,0.02366021],"category_scores_gemma":[0.01279929,0.0003501659,0.0005700845,0.002579827,0.005607911,0.01242405,0.002966945,0.002899393,0.001369338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002967619,"about_ca_system_score_gemma":0.001539942,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009760234,"about_ca_topic_score_gemma":0.006106599,"domain_scores_codex":[0.999166,0.0004088079,0.00002334603,0.0001417868,0.0001472073,0.0001128121],"domain_scores_gemma":[0.9968495,0.001737814,0.0003996069,0.0004378159,0.0003502317,0.0002250554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00001065695,0.000005946735,0.0003431921,0.0000154339,0.000005061707,0.00002733636,0.0001517345,0.001019398,0.00003218394,0.991742,0.003795451,0.002851722],"study_design_scores_gemma":[0.000007154849,0.000004503878,0.0004033239,0.00001905187,0.000004431909,0.0000417855,0.0003326297,0.00189239,0.00002628368,0.9845837,0.01267977,0.000004972637],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.09389666,0.01119993,0.1552373,0.2147627,0.001697794,0.0000944842,0.002226664,0.0003828096,0.5205017],"genre_scores_gemma":[0.9535013,0.004042065,0.01224551,0.002743955,0.0009169074,0.00005529657,0.0002701152,0.0001545437,0.02607022],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02366021,"threshold_uncertainty_score":0.07915127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1569316879786181,"score_gpt":0.3512541636628392,"score_spread":0.1943224756842211,"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."}}