{"id":"W4253611031","doi":"10.32920/ryerson.14655489.v1","title":"Light rail transit as a tool for urban brownfield revitalization","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Brownfield; Urban sprawl; Environmental planning; Business; Transport engineering; Investment (military); Sustainability; Urban planning; Transit (satellite); Urban regeneration; Rail transit; Public transport; Geography; Civil engineering; Engineering; Redevelopment; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0008527547,0.0001311203,0.00007873736,0.0008135247,0.00213385,0.002248637,0.0005398317,0.0005878962,0.01034322],"category_scores_gemma":[0.001540194,0.0001103697,0.0001560788,0.001268367,0.001791024,0.00142411,0.002516825,0.0005900507,0.0004311724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005303794,"about_ca_system_score_gemma":0.008084005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04532633,"about_ca_topic_score_gemma":0.1350164,"domain_scores_codex":[0.9993777,0.0002907759,0.000009290766,0.00003486981,0.00008423945,0.0002031514],"domain_scores_gemma":[0.9993759,0.000167507,0.00008636701,0.00006100683,0.00008463395,0.0002247193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004334207,0.001239927,0.08658803,0.0003973641,0.00004206983,0.003862875,0.03080907,0.01313192,0.004071945,0.5007403,0.04731712,0.3113659],"study_design_scores_gemma":[0.0001606087,0.001171623,0.1788965,0.0006085242,0.00005428018,0.00107754,0.1530027,0.01666516,0.005641514,0.03665191,0.6059754,0.00009427215],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.8170566,0.0005095414,0.004541186,0.008992886,0.00006140199,0.0002855643,0.0001494386,0.0001999395,0.1682035],"genre_scores_gemma":[0.9836948,0.0002045142,0.001606072,0.0001581856,0.0000110009,0.00005336954,0.00004708588,0.00001414022,0.01421065],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04532633,"threshold_uncertainty_score":0.09012496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0281760541979635,"score_gpt":0.311367573596474,"score_spread":0.2831915193985106,"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."}}