{"id":"W2061649002","doi":"10.1002/atr.106","title":"Model of personal attitudes towards transit service quality","year":2010,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Toronto","funders":"","keywords":"Multinomial logistic regression; Transit (satellite); Reliability (semiconductor); Latent variable; Service quality; Transport engineering; Perception; Service (business); Public transport; Quality (philosophy); Business; Computer science; Marketing; Psychology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001282528,0.0006646605,0.0004387251,0.0009239722,0.0006386166,0.002526531,0.001395798,0.0009528138,0.0248714],"category_scores_gemma":[0.00473776,0.000382732,0.0009858729,0.0009722734,0.001204516,0.001204017,0.0008542211,0.001492357,0.002805041],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002944951,"about_ca_system_score_gemma":0.001305688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0872819,"about_ca_topic_score_gemma":0.03831086,"domain_scores_codex":[0.9990319,0.0003485902,0.00002730602,0.0002289501,0.0001545786,0.0002087197],"domain_scores_gemma":[0.9978222,0.001076963,0.0003201458,0.0001563999,0.0004607133,0.000163732],"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":[0.000461863,0.0005741458,0.1586954,0.0001605017,0.0003797016,0.0009754152,0.005512284,0.5300609,0.001395427,0.2412177,0.01010005,0.05046659],"study_design_scores_gemma":[0.00007503204,0.0001162312,0.03466179,0.00006003382,0.00009317234,0.0001802796,0.001038256,0.9285125,0.0001647532,0.02879201,0.006250912,0.00005512314],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7103227,0.000496582,0.1938222,0.005113523,0.0001199999,0.0003382173,0.004792168,0.0007946352,0.08420007],"genre_scores_gemma":[0.971532,0.0002159934,0.004030267,0.00008557328,0.00003201509,0.0001389201,0.0007029871,0.00002268563,0.02323963],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0872819,"threshold_uncertainty_score":0.1735477,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04480772207004855,"score_gpt":0.3582700714044495,"score_spread":0.3134623493344009,"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."}}