{"id":"W7066141959","doi":"","title":"Evaluating Affordable Housing Outcomes in Toronto: An Analysis of Density Bonusing Agreements","year":2022,"lang":"en","type":"other","venue":"TSpace","topic":"Knowledge Societies in the 21st Century","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Toronto; University of Florida","keywords":"Corporate governance; Government (linguistics); Affordable housing; Work (physics); Payment","routes":{"ca_aff":false,"ca_fund":true,"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":[0.005054135,0.0004276486,0.0004488888,0.002850659,0.002481067,0.002782991,0.001175498,0.0005505615,0.003585607],"category_scores_gemma":[0.02200422,0.0002607469,0.0007293025,0.006853157,0.001956675,0.001259319,0.002733556,0.001184863,0.0002967765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06903484,"about_ca_system_score_gemma":0.02200294,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9154655,"about_ca_topic_score_gemma":0.9411932,"domain_scores_codex":[0.9925737,0.001364258,0.0003524589,0.0003280803,0.003951291,0.001430084],"domain_scores_gemma":[0.9669833,0.009008504,0.007756594,0.001070533,0.01152953,0.003651473],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005543552,0.0003705834,0.9137076,0.0004109533,0.0003420515,0.0006497639,0.01560663,0.01576545,0.0005071224,0.01286587,0.008140234,0.03107934],"study_design_scores_gemma":[0.00002233924,0.0001974493,0.9770398,0.00009177755,0.00006012378,0.00002921839,0.01182909,0.004435005,0.0001996781,0.0003873779,0.005682207,0.00002582151],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9735771,0.0005354637,0.0005345035,0.0006394242,0.0000149385,0.0002872874,0.003692801,0.00002423443,0.02069426],"genre_scores_gemma":[0.9935564,0.0003254519,0.0004621405,0.00006771021,0.000009552436,0.0001455071,0.002682498,0.000008174902,0.002742497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08453453,"threshold_uncertainty_score":0.5008852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05955579760974135,"score_gpt":0.4634624733831457,"score_spread":0.4039066757734044,"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."}}