{"id":"W3040457335","doi":"10.1111/tesg.12449","title":"Mega Regions and Pandemics","year":2020,"lang":"en","type":"article","venue":"Tijdschrift voor Economische en Sociale Geografie","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mega-; Megacity; Pandemic; Metropolitan area; Coronavirus disease 2019 (COVID-19); Urbanization; Economic geography; Geography; 2019-20 coronavirus outbreak; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Economic growth; Development economics; Disease; Economy; Infectious disease (medical specialty); Economics; Outbreak; Medicine; Virology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008486229,0.0003231662,0.0007971394,0.0000379831,0.0003552643,0.00005795943,0.0003228626,0.0003227576,0.0002235537],"category_scores_gemma":[0.00562951,0.0002979616,0.000235683,0.0001606556,0.0002998052,0.0001504229,0.0004412902,0.0004879737,0.00009096703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005047256,"about_ca_system_score_gemma":0.00008899144,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001319772,"about_ca_topic_score_gemma":0.0001492534,"domain_scores_codex":[0.997947,0.0002137784,0.0006008378,0.0006077069,0.0001132953,0.0005173931],"domain_scores_gemma":[0.9957137,0.003366642,0.0002589077,0.000280348,0.00005699151,0.0003234395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001585331,0.0002105,0.111254,0.0004552406,0.0009134535,0.0000329352,0.006173402,0.00002350245,0.0003177324,0.6791209,0.1851549,0.01618495],"study_design_scores_gemma":[0.001913775,0.0001960921,0.01405377,0.00003296433,0.0002512008,0.000007070603,0.001343647,0.0007054462,0.0000915796,0.1958854,0.7846144,0.0009046058],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8593381,0.001971103,0.004460718,0.09561767,0.0003127809,0.001201008,0.0001050801,0.001118092,0.03587547],"genre_scores_gemma":[0.9792675,0.0009286243,0.007568464,0.009913902,0.00121312,0.0001112291,0.00001273239,0.00006563999,0.0009187579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5994595,"threshold_uncertainty_score":0.9999472,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2100161292001335,"score_gpt":0.3779490752929281,"score_spread":0.1679329460927946,"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."}}