{"id":"W7052978202","doi":"","title":"Toronto’s Golden Mile Urban Redevelopment Project: Intensifying Social Exclusions or Increasing Opportunity?","year":2024,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Nuclear reactor physics and engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Redevelopment; Urban planning; Mile; Urban regeneration; Urban poverty; Government (linguistics)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002563887,0.000288536,0.0003245067,0.0007064046,0.01317561,0.006317779,0.001319272,0.002776447,0.03868692],"category_scores_gemma":[0.003976372,0.0002291564,0.0003137373,0.00115631,0.005332848,0.001830822,0.00496027,0.002377864,0.002164973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02384255,"about_ca_system_score_gemma":0.08650321,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.7805966,"about_ca_topic_score_gemma":0.9593199,"domain_scores_codex":[0.9977775,0.0004313209,0.00002097383,0.00008938902,0.0003467395,0.00133409],"domain_scores_gemma":[0.9898257,0.000519259,0.0001934941,0.0001653572,0.0004384119,0.008857846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0003194145,0.0004067322,0.02408737,0.0001343483,0.0000307256,0.0006989973,0.02777772,0.0002967825,0.000488552,0.07454431,0.7619411,0.1092739],"study_design_scores_gemma":[0.0001147162,0.0001244379,0.1377826,0.000254966,0.00004479927,0.00008706093,0.1028844,0.0002562502,0.0003591139,0.00662434,0.7514168,0.00005064846],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2494428,0.002978097,0.0003469915,0.3149892,0.001783782,0.0001781784,0.001347079,0.0001206327,0.4288132],"genre_scores_gemma":[0.7153436,0.002598877,0.0006323651,0.02735151,0.0005086561,0.0001955917,0.0005548854,0.0001191233,0.2526954],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.2194034,"threshold_uncertainty_score":0.4413911,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02914278996945672,"score_gpt":0.251165294937213,"score_spread":0.2220225049677563,"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."}}