{"id":"W4391617839","doi":"10.32920/25169600.v1","title":"COVID-19 in Toronto: Investigating the Spatial Impact of Retailers in the Food Retail and Food Service Sector","year":2024,"lang":"en","type":"preprint","venue":"","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Downtown; Business; Spatial analysis; Distribution (mathematics); Marketing; Spatial distribution; Geography; Tertiary sector of the economy; Economic geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0003283056,0.00024507,0.0002082437,0.0009197784,0.000689349,0.0009350993,0.0004619402,0.0002713486,0.002075953],"category_scores_gemma":[0.001784461,0.0001807564,0.0003395994,0.002610419,0.0007246462,0.0004408209,0.001223293,0.0003583997,0.0001948033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009511159,"about_ca_system_score_gemma":0.004628099,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9317998,"about_ca_topic_score_gemma":0.9485304,"domain_scores_codex":[0.9996309,0.00008066095,0.00001645876,0.00005010526,0.00007548919,0.0001463794],"domain_scores_gemma":[0.9988645,0.0002174143,0.0003698286,0.00005348963,0.0002692809,0.0002255067],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006978758,0.00003299146,0.9881288,0.0000482418,0.00006687021,0.0005471347,0.001351739,0.00423606,0.0003169705,0.0008443799,0.001068741,0.00328829],"study_design_scores_gemma":[0.00000334581,0.00003648792,0.9866523,0.00002261516,0.0000283699,0.00006845154,0.00676258,0.005139105,0.0001254432,0.0001026599,0.001049508,0.000009130886],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9968337,0.0002141594,0.0002280796,0.0002143312,0.000004415471,0.00001689046,0.001241294,0.000003939963,0.001243244],"genre_scores_gemma":[0.997903,0.0001828575,0.0001426722,0.00001407797,0.000003185742,0.000005879303,0.0009494081,0.00000170966,0.0007972813],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06820017,"threshold_uncertainty_score":0.1372036,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1140674358355675,"score_gpt":0.3075580838781211,"score_spread":0.1934906480425536,"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."}}