{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005245073,0.001027602,0.0008835023,0.000343172,0.0008881739,0.0002509592,0.0005774947,0.0007697308,0.0004185619],"category_scores_gemma":[0.0002724513,0.001063214,0.0003502748,0.0005765193,0.00002660118,0.0009735177,0.0002562788,0.001858318,0.0001472096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002586668,"about_ca_system_score_gemma":0.0001602486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001297258,"about_ca_topic_score_gemma":0.002199652,"domain_scores_codex":[0.9965158,0.00008056605,0.0009100506,0.0008360126,0.0007076028,0.0009499519],"domain_scores_gemma":[0.9985976,0.0001167109,0.000165568,0.0004913835,0.0002375178,0.0003911965],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005483396,0.0003922581,0.000006882586,0.007771747,0.003329616,0.001238362,0.001860393,0.0003226163,0.3470073,0.06875223,0.003867883,0.5649024],"study_design_scores_gemma":[0.0009114422,0.0001368676,0.0003977303,0.003986349,0.0007456761,0.0001236852,0.0058961,0.002361294,0.0105361,0.002523351,0.9680312,0.004350267],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6866571,0.0007744301,6.178118e-7,0.000008950063,0.004787957,0.000842441,0.0007667028,0.002243436,0.3039183],"genre_scores_gemma":[0.988094,0.0005779014,0.0008001415,0.00006021865,0.0003788745,0.0001713238,0.001520685,0.0008143021,0.007582546],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9641632,"threshold_uncertainty_score":0.9991818,"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."}}