{"id":"W3160523774","doi":"10.32866/001c.24072","title":"Changes in Transit Accessibility to Food Banks in Toronto during COVID-19","year":2021,"lang":"en","type":"article","venue":"Findings","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Coronavirus disease 2019 (COVID-19); Food insecurity; Public transport; 2019-20 coronavirus outbreak; Pandemic; Food supply; Business; Transit (satellite); Low income; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); Food security; Geography; Agricultural economics; Socioeconomics; Medicine; Economics; Transport engineering; Engineering; Agriculture; Virology","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":[0.0002005378,0.0001964648,0.0001748392,0.0008283285,0.00149487,0.0009702265,0.000475318,0.0003408289,0.002926116],"category_scores_gemma":[0.001832824,0.0001620985,0.0002855465,0.002218937,0.0006856341,0.0004883098,0.00104439,0.0005481419,0.0002286444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01402012,"about_ca_system_score_gemma":0.006389989,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9652464,"about_ca_topic_score_gemma":0.9868211,"domain_scores_codex":[0.9996,0.00004240891,0.00002452261,0.00005564868,0.00009595673,0.0001814815],"domain_scores_gemma":[0.9986724,0.0001062951,0.000403394,0.000036794,0.0004298885,0.0003512736],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001599284,0.00003728606,0.9666957,0.0001714446,0.0000589559,0.0003651194,0.01384517,0.0005364938,0.0006953175,0.0004023057,0.005347221,0.01168512],"study_design_scores_gemma":[0.000001053412,0.00001149139,0.9937989,0.00002728431,0.000006264627,0.00002131415,0.005090329,0.00007110064,0.00003656769,0.000009140947,0.0009218608,0.000004842739],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.990139,0.0004403121,0.00007957225,0.0006577038,0.0000147344,0.0000231638,0.00398314,0.00001496816,0.004647366],"genre_scores_gemma":[0.9977332,0.0002346848,0.00006569824,0.00005092385,0.000004618422,0.00001152023,0.0008437836,0.000003160654,0.001052249],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03475362,"threshold_uncertainty_score":0.1017236,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04498640756139525,"score_gpt":0.3417946113831195,"score_spread":0.2968082038217242,"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."}}