{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008268676,0.0001449841,0.0002017749,0.001311488,0.0007307279,0.001643158,0.0002471627,0.000552476,0.01072407],"category_scores_gemma":[0.004290216,0.0001254549,0.0002022067,0.002508041,0.001463255,0.002108985,0.001898395,0.0008449737,0.0002728129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001082462,"about_ca_system_score_gemma":0.0006500076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007808035,"about_ca_topic_score_gemma":0.009696481,"domain_scores_codex":[0.999351,0.0003837993,0.00002120877,0.00006416751,0.00007527872,0.0001045872],"domain_scores_gemma":[0.9980296,0.0009839794,0.0005485758,0.0001071504,0.0001186678,0.0002120089],"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":[0.0001244427,0.000071956,0.1491502,0.0007121621,0.000174913,0.0005026789,0.008118844,0.003039919,0.0002481072,0.7584127,0.01455249,0.0648917],"study_design_scores_gemma":[0.00003518562,0.0001657663,0.4165502,0.00147662,0.0001118513,0.0009599819,0.05016232,0.003579851,0.0002751334,0.2925377,0.2340914,0.00005398616],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6658356,0.05646857,0.01024459,0.05607954,0.0005938574,0.00008798009,0.002503637,0.00005422582,0.208132],"genre_scores_gemma":[0.9791749,0.0157246,0.001197657,0.0008252806,0.0002286694,0.00003485859,0.0002271774,0.000009167462,0.002577629],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01072407,"threshold_uncertainty_score":0.03587556,"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."}}