{"id":"W2913201573","doi":"10.1080/10630732.2018.1558573","title":"Examining Open Data at the Urban Level: An Exploration of “Wellbeing Toronto”","year":2019,"lang":"en","type":"article","venue":"Journal of Urban Technology","topic":"E-Government and Public Services","field":"Social Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Urban studies; Regional science; Environmental planning; Sociology; Data science; Geography; Computer science; Economic growth; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002064842,0.00007700468,0.0002180446,0.00006955136,0.0001948828,0.00009596559,0.003084099,0.0001531953,0.0005160513],"category_scores_gemma":[0.0001973025,0.0000551374,0.00002493513,0.0002403023,0.0001946686,0.004058185,0.0008531693,0.0001696876,0.00001075043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001826443,"about_ca_system_score_gemma":0.0001598233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001787265,"about_ca_topic_score_gemma":0.01452824,"domain_scores_codex":[0.9987027,0.0001416122,0.0003720638,0.0001571065,0.0004357656,0.0001907766],"domain_scores_gemma":[0.9983642,0.0001346253,0.0007443831,0.0005723747,0.0001378597,0.00004656156],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002150013,0.0002962759,0.6306161,0.00003662718,0.0002566841,0.00001434076,0.05044026,0.00001423932,0.01351648,0.192629,0.04782762,0.06413735],"study_design_scores_gemma":[0.001329624,0.0011441,0.01147191,0.0001461942,0.00009096036,0.00001593158,0.2976196,0.0001474291,0.003522006,0.007455812,0.6767395,0.0003169422],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9663875,0.00122298,0.0001015571,0.007538126,0.0005965003,0.0002428002,0.00001108269,0.00002607106,0.02387334],"genre_scores_gemma":[0.9962065,0.0001700881,0.0006662844,0.0001258124,0.000244235,0.00000153279,0.000006061065,0.000009232273,0.00257031],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6289118,"threshold_uncertainty_score":0.8107099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1759195687748804,"score_gpt":0.3596441677887415,"score_spread":0.1837245990138611,"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."}}