{"id":"W2556016565","doi":"10.3141/2568-10","title":"Moving Beyond Evaluation to Transit Project Prioritization: Lessons from the Toronto, Ontario, Canada, Context","year":2016,"lang":"en","type":"article","venue":"Transportation Research Record Journal of the Transportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dillon Consulting","funders":"","keywords":"Transportation planning; Context (archaeology); Interdependence; Agency (philosophy); Process (computing); Prioritization; Business; Process management; Transport engineering; Risk analysis (engineering); Management science; Computer science; Economics; Engineering; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02228638,0.001025267,0.001086281,0.003704559,0.01373064,0.0124328,0.004050673,0.001803348,0.004055647],"category_scores_gemma":[0.04326473,0.0006738456,0.0007770268,0.01270109,0.01041764,0.003986022,0.004460647,0.00306801,0.0002446803],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.389776,"about_ca_system_score_gemma":0.4783142,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9970549,"about_ca_topic_score_gemma":0.998821,"domain_scores_codex":[0.9711125,0.01136998,0.001302495,0.001231327,0.008294974,0.006688705],"domain_scores_gemma":[0.9509419,0.01674255,0.001789466,0.001437676,0.02454901,0.004539379],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.0005540159,0.0004721834,0.09449164,0.003814595,0.0003561582,0.003046687,0.05599315,0.03916981,0.00114881,0.3395225,0.143385,0.3180454],"study_design_scores_gemma":[0.0004038086,0.0004583573,0.227784,0.006018926,0.0004867676,0.0005738834,0.1906449,0.02174592,0.002062493,0.07519005,0.4741122,0.0005186043],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2717996,0.04281671,0.03289093,0.2435877,0.001171047,0.003210958,0.004150628,0.0004565195,0.3999159],"genre_scores_gemma":[0.9408211,0.01300751,0.01988047,0.005561226,0.0001365389,0.0004892208,0.0007943466,0.0001519537,0.01915769],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.389776,"threshold_uncertainty_score":0.7077733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1126299993335747,"score_gpt":0.4115247462752259,"score_spread":0.2988947469416512,"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."}}