{"id":"W594725858","doi":"","title":"TORONTO IN TRANSIT: A TALE OF TWO SYSTEMS","year":2003,"lang":"en","type":"article","venue":"Railway age","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transit (satellite); Transit system; Transport engineering; Rail transit; Bus rapid transit; Rapid transit; Light rail transit; Mile; Public transport; Urban transit; Business; Engineering; Geography","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":[0.001075528,0.000971565,0.0004076948,0.001363031,0.007197344,0.01130881,0.001095008,0.00243739,0.02384118],"category_scores_gemma":[0.001820975,0.0005090117,0.000585413,0.002684661,0.00467519,0.005293005,0.005052164,0.002688821,0.002487043],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03010521,"about_ca_system_score_gemma":0.02044407,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.4828151,"about_ca_topic_score_gemma":0.6016406,"domain_scores_codex":[0.9983588,0.0003849693,0.00005746863,0.0002016344,0.0005513281,0.0004458611],"domain_scores_gemma":[0.9989591,0.00007865769,0.00004212315,0.00007776354,0.0002748016,0.0005675534],"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":[0.0001075734,0.00005415614,0.00385387,0.0002925707,0.00007109477,0.0005652027,0.004938188,0.009665597,0.0008672894,0.6153891,0.2662024,0.09799308],"study_design_scores_gemma":[0.00001305888,0.00005094644,0.001792289,0.0001393636,0.00003749046,0.0001112297,0.003916345,0.002893594,0.0002971797,0.04451433,0.9461829,0.0000512211],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0309823,0.02606671,0.04634244,0.1644387,0.005981173,0.0003513606,0.001862411,0.001127051,0.7228478],"genre_scores_gemma":[0.4987438,0.03337866,0.04289079,0.013821,0.001600948,0.0002790744,0.002027161,0.0007631123,0.4064955],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5171849,"threshold_uncertainty_score":0.9600097,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673534222707353,"score_gpt":0.2891672292488122,"score_spread":0.2724318870217387,"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."}}