{"id":"W2372236441","doi":"","title":"Influencing Factors of City Bus Service Quality Based on SERVPERF Model","year":2013,"lang":"en","type":"article","venue":"Journal of Transportation Systems Engineering and Information Technology","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Reliability (semiconductor); Dimension (graph theory); Service quality; Service (business); Empathy; Perception; Scale (ratio); Quality (philosophy); Business; Transport engineering; Computer science; Marketing; Psychology; Engineering; Mathematics; Social psychology; Geography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004348877,0.00008872408,0.0002139954,0.0005541196,0.00008139535,0.00003423457,0.0001035995,0.0001716973,0.000007650096],"category_scores_gemma":[0.00008414723,0.00008186315,0.00003889812,0.0004445675,0.00002840368,0.001392657,7.203749e-7,0.0001540009,0.000001079187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003905663,"about_ca_system_score_gemma":0.00009736615,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004689033,"about_ca_topic_score_gemma":0.00001985421,"domain_scores_codex":[0.9986993,0.00001957622,0.0008078715,0.00004908551,0.0003135011,0.000110674],"domain_scores_gemma":[0.9984547,0.00006457417,0.0006048306,0.00007173975,0.0007413261,0.00006275273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009347325,0.00001022996,0.01775914,0.0001438683,0.00001180408,1.492614e-7,0.005695859,0.9689317,0.0001957656,0.007002851,0.00001253027,0.0002267043],"study_design_scores_gemma":[0.001393136,0.0001941112,0.248193,0.0006055453,0.00005719609,0.000002593589,0.02067489,0.7249593,0.001324786,0.0001298377,0.002099804,0.0003657558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8742095,0.00002452799,0.1249362,0.0003510184,0.0001355202,0.0001350949,0.00002013333,0.00007091901,0.0001170776],"genre_scores_gemma":[0.9972958,0.00002522773,0.002577398,0.00004917918,0.00001158809,0.000005651876,0.00002484602,0.000004447273,0.00000583748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2439724,"threshold_uncertainty_score":0.3338282,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01362208864210281,"score_gpt":0.2401748140088175,"score_spread":0.2265527253667146,"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."}}