{"id":"W3144005709","doi":"","title":"Mode Substitution Effect of Urban Cycle Tracks: Case Study of a Downtown Street in Toronto, Canada","year":2016,"lang":"en","type":"article","venue":"Transportation Research Board 95th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto Metropolitan University","funders":"","keywords":"Downtown; Redevelopment; Transport engineering; Cycling; Mode choice; Mode (computer interface); Sample (material); Travel survey; Travel behavior; Geography; Engineering; Public transport; Computer science; Civil engineering","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":[0.0004621778,0.0004131938,0.000328511,0.001031488,0.006082397,0.001265358,0.001365824,0.0007909404,0.002200585],"category_scores_gemma":[0.001305217,0.0002881956,0.0003599255,0.002816648,0.001371215,0.0004255074,0.001039094,0.0006243977,0.0001662267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03070216,"about_ca_system_score_gemma":0.02547798,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9795789,"about_ca_topic_score_gemma":0.9944968,"domain_scores_codex":[0.999102,0.000181267,0.00003154412,0.0001045199,0.0002238303,0.0003568349],"domain_scores_gemma":[0.9988855,0.0001864989,0.0001249551,0.00005162137,0.0004153239,0.0003361311],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003495498,0.0009166999,0.7802666,0.0005863999,0.0001398429,0.0559844,0.105435,0.005876735,0.005399544,0.003250935,0.004875329,0.036919],"study_design_scores_gemma":[0.00003456825,0.0004816774,0.679884,0.0002578415,0.0001110569,0.003252946,0.2924673,0.005605118,0.001297324,0.0002494696,0.01626708,0.00009158371],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966048,0.000122741,0.0002294256,0.0001668709,0.000005526946,0.00009671516,0.0002545438,0.00000474181,0.002514523],"genre_scores_gemma":[0.996124,0.0003212309,0.0005721581,0.00009055981,0.000003409604,0.0000319368,0.0001937465,0.000005710868,0.002657194],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03070216,"threshold_uncertainty_score":0.2227608,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0359978557238158,"score_gpt":0.403546145279898,"score_spread":0.3675482895560822,"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."}}