{"id":"W2301368578","doi":"","title":"Loyalty in Transit: An Analysis of Bus and Rail Users in Two Canadian Cities","year":2016,"lang":"en","type":"article","venue":"Transportation Research Board 95th Annual MeetingTransportation Research Board","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Loyalty; Attractiveness; Customer satisfaction; Transit (satellite); Marketing; Business; Service quality; Public transport; Advertising; Perception; Quality (philosophy); Order (exchange); Loyalty business model; Structural equation modeling; Service (business); Transport engineering; Psychology; Computer science; Engineering","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":[0.001051648,0.0003222616,0.0004984033,0.001863725,0.003801824,0.001763029,0.001025121,0.0008026907,0.001451221],"category_scores_gemma":[0.002680588,0.0004032516,0.0007023083,0.005057416,0.000910865,0.000668739,0.001109202,0.0009940735,0.0002836196],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01570229,"about_ca_system_score_gemma":0.01378532,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9809738,"about_ca_topic_score_gemma":0.9879963,"domain_scores_codex":[0.9988583,0.000117326,0.00005513231,0.0001009692,0.0003542574,0.0005139521],"domain_scores_gemma":[0.9971223,0.0002467106,0.0003935647,0.0000780176,0.001404839,0.0007543999],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00007951108,0.0001204658,0.986873,0.00001820628,0.00002518301,0.00008603176,0.008422001,0.00009777484,0.000199068,0.00007585198,0.0003659317,0.003637048],"study_design_scores_gemma":[0.000002479972,0.0000415494,0.9862815,0.000007242996,0.00001157451,0.00002687588,0.01286539,0.0003195527,0.00003550599,0.000008155745,0.0003872889,0.0000128814],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992276,0.00003043284,0.00002719202,0.00004571948,0.000001568156,0.00001834984,0.0002847031,0.000001502344,0.0003629513],"genre_scores_gemma":[0.9986386,0.00006675422,0.00007072599,0.00004470832,0.000001877649,0.00002026923,0.000601457,0.000002846785,0.0005528639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01902622,"threshold_uncertainty_score":0.1139286,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05850648834711938,"score_gpt":0.4074036571596316,"score_spread":0.3488971688125122,"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."}}