{"id":"W2007908002","doi":"10.1061/40717(148)32","title":"Transit in the Greater Toronto Area: Overview and Challenges","year":2004,"lang":"en","type":"article","venue":"","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Geography; Government (linguistics); Regional science; Population; Public transport; Transport engineering; Engineering; Demography; Sociology","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":[0.0004092248,0.0006656557,0.0003149798,0.002106414,0.00190441,0.003566582,0.0008112716,0.001120539,0.004332678],"category_scores_gemma":[0.0006848785,0.0002937944,0.0003362433,0.007372316,0.001102098,0.002005813,0.001105155,0.0009983301,0.0003817957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01720226,"about_ca_system_score_gemma":0.01544467,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8439473,"about_ca_topic_score_gemma":0.9149054,"domain_scores_codex":[0.9994826,0.00008304686,0.0000247866,0.00006333207,0.0001848575,0.0001612884],"domain_scores_gemma":[0.9992241,0.0001359117,0.00009339335,0.00001722037,0.0003209893,0.0002084336],"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":[0.0001971929,0.0001206394,0.08813158,0.007863476,0.0001963745,0.002872383,0.004575562,0.06356387,0.002194471,0.1372228,0.204512,0.4885497],"study_design_scores_gemma":[0.00001232727,0.0001908407,0.1132797,0.001688326,0.0001531529,0.001516386,0.01379838,0.02859123,0.0006080365,0.009196728,0.8308537,0.0001111603],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1307445,0.6049876,0.01222465,0.0752882,0.00152688,0.0002664612,0.004185589,0.0002761823,0.1704999],"genre_scores_gemma":[0.4817325,0.4829873,0.005133266,0.001268388,0.001771162,0.00007610987,0.002108503,0.00005024064,0.02487268],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1560527,"threshold_uncertainty_score":0.3139434,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08462856579631088,"score_gpt":0.3007599419788641,"score_spread":0.2161313761825532,"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."}}