{"id":"W2904296272","doi":"10.36939/cjur/vol27no1/art113","title":"Regional Planning and Urban Revitalization in Mid-Sized Cities: A Case Study on Downtown Guelph","year":2018,"lang":"en","type":"article","venue":"Canadian journal of urban research","topic":"Facilities and Workplace Management","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Journal of Administrative Sciences","funders":"","keywords":"Downtown; Plan (archaeology); Incentive; Urban planning; Geography; Investment (military); Economic growth; Comprehensive planning; Environmental planning; Political science; Regional science; Business; Civil engineering; Engineering; Economics; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0007625776,0.0003204043,0.0002747712,0.0006054352,0.01240796,0.002204171,0.001804238,0.001126695,0.002898175],"category_scores_gemma":[0.001549369,0.0002824275,0.0002596415,0.001563509,0.004406522,0.0006949698,0.002665522,0.001345344,0.0001593866],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04129275,"about_ca_system_score_gemma":0.025341,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9372972,"about_ca_topic_score_gemma":0.9886962,"domain_scores_codex":[0.9986676,0.0004788272,0.00002412648,0.0001025301,0.0001618044,0.0005650491],"domain_scores_gemma":[0.9989212,0.0002549441,0.0001011381,0.00005080998,0.0001929967,0.0004789702],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001724606,0.0005879242,0.1000657,0.0003607066,0.00003177351,0.03416998,0.7864876,0.001841451,0.001994244,0.02274272,0.01490743,0.03663795],"study_design_scores_gemma":[0.00001645933,0.0001306854,0.06949895,0.0001378623,0.00001438218,0.001039274,0.8722606,0.0005399545,0.0002742061,0.0004136589,0.0556468,0.00002706036],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9816266,0.0004188211,0.0002046029,0.001512551,0.0000168449,0.0001041827,0.00006636634,0.000007053267,0.016043],"genre_scores_gemma":[0.9901322,0.0006486314,0.0005471812,0.0003250229,0.00000380934,0.000052136,0.00004806632,0.00000736598,0.008235586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06270283,"threshold_uncertainty_score":0.2996012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1441181284449709,"score_gpt":0.4002291220714819,"score_spread":0.256110993626511,"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."}}