{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008611435,0.0001027183,0.000290299,0.00007268352,0.0001265043,0.00001405107,0.0002348859,0.0001106603,0.0001698078],"category_scores_gemma":[0.00003276612,0.00009362844,0.0002045654,0.0002534084,0.0001469732,0.001035059,6.426716e-7,0.0003306688,6.351618e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002467524,"about_ca_system_score_gemma":0.0004167199,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000522662,"about_ca_topic_score_gemma":0.02073332,"domain_scores_codex":[0.9982968,0.00003997754,0.0007087807,0.0001295069,0.0006571356,0.0001678278],"domain_scores_gemma":[0.9984668,0.00004698322,0.0005170638,0.00009033396,0.0007494581,0.000129383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001047526,0.0007688949,0.5081431,0.0004484307,0.0001138108,0.00001060886,0.1304707,0.02087105,0.3109826,0.005250657,0.00001253567,0.0218801],"study_design_scores_gemma":[0.0007166137,0.00004295153,0.9911116,0.00003840968,0.00006491136,2.595511e-7,0.00226196,0.00008298483,0.003060952,0.002314819,0.000184632,0.0001198593],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9938692,0.0000522617,0.004242551,0.0008867455,0.0003475813,0.0001051951,0.00004389373,0.0000152431,0.0004372625],"genre_scores_gemma":[0.9906547,0.00004333539,0.009028522,0.00007516001,0.0001394642,0.000001438499,0.00001072948,0.000008361269,0.0000382946],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4829686,"threshold_uncertainty_score":0.9971358,"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."}}