{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.01034898,0.0003089734,0.0006918035,0.007060287,0.0007001776,0.0001198551,0.0005587785,0.000320015,0.0004637804],"category_scores_gemma":[0.0004957529,0.0002994501,0.0001608952,0.007371918,0.001647887,0.001426264,0.000003328387,0.0008201759,0.000009375329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000475294,"about_ca_system_score_gemma":0.001785647,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8234367,"about_ca_topic_score_gemma":0.995744,"domain_scores_codex":[0.9910195,0.001861588,0.001377877,0.001010634,0.002986379,0.001744041],"domain_scores_gemma":[0.994652,0.001486218,0.0001817533,0.0003965099,0.002240355,0.001043168],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006490148,0.0001450229,0.9061357,0.00008264253,0.00009222452,0.0001037019,0.06414683,0.01240941,0.0002805761,0.01313579,0.00005302277,0.002766048],"study_design_scores_gemma":[0.001887555,0.0001840261,0.9608986,0.0002479921,0.00007400926,5.192874e-8,0.03338083,0.0007505062,0.0001273759,0.0008141613,0.001298968,0.0003359037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9932079,0.0001270875,0.0007118231,0.002675117,0.00007749207,0.001142621,0.0008638455,0.00008490459,0.001109224],"genre_scores_gemma":[0.9970574,0.0007493278,0.001063365,0.00004948335,0.00005119529,0.00018733,0.0004521063,0.00004817516,0.0003415754],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1723074,"threshold_uncertainty_score":0.9999458,"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."}}