{"id":"W1991879121","doi":"10.1068/b2620","title":"Shaping Metropolitan Toronto: A Study of Linear Infrastructure Subsidies, 1954–66","year":2000,"lang":"en","type":"article","venue":"Environment and Planning B Planning and Design","topic":"Urbanization and City Planning","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Metropolitan area; Subsidy; Jurisdiction; Suburbanization; Government (linguistics); Regional science; Business; Redevelopment; Geography; Political science; Civil engineering; Engineering","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":[0.000658528,0.0002175494,0.000224309,0.001325138,0.00868617,0.003089009,0.0009218714,0.0007209036,0.005952389],"category_scores_gemma":[0.002885336,0.0003508865,0.0001634226,0.00458574,0.004455045,0.001342485,0.002497225,0.001410111,0.0002798772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.08481797,"about_ca_system_score_gemma":0.02296146,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9702861,"about_ca_topic_score_gemma":0.9890854,"domain_scores_codex":[0.99925,0.0001691498,0.0000160974,0.00006208685,0.0001108687,0.0003917791],"domain_scores_gemma":[0.9986595,0.0002674404,0.0002900606,0.00007058542,0.0002736821,0.000438809],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0001356948,0.00009691438,0.1405195,0.0001302385,0.00003914731,0.001655625,0.7217592,0.001345669,0.0006126603,0.08059543,0.02260966,0.03050029],"study_design_scores_gemma":[0.0000141935,0.00004005877,0.4428017,0.0001342467,0.00002148392,0.0001865654,0.3468033,0.0004345484,0.0002453936,0.001438297,0.2078484,0.00003180639],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9379501,0.00197249,0.0002865606,0.005501301,0.00004747771,0.000049405,0.000722746,0.00001253766,0.05345741],"genre_scores_gemma":[0.9864944,0.0009693896,0.00009572963,0.0002322328,0.00001602175,0.0000277368,0.0002054221,0.00001111962,0.01194803],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08481797,"threshold_uncertainty_score":0.6154003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04522174446405938,"score_gpt":0.289511664270007,"score_spread":0.2442899198059476,"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."}}