{"id":"W14351696","doi":"10.1111/j.1476-5381.1955.tb00069.x","title":"Why Do People Use Transit? Model for Explanation of Personal Attitude Toward Transit Service Quality","year":2009,"lang":"en","type":"article","venue":"Transportation Research Board 88th Annual MeetingTransportation Research Board","topic":"Urban Transport and Accessibility","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Multinomial logistic regression; Transit (satellite); Reliability (semiconductor); Latent variable; Service quality; Perception; Service (business); Transport engineering; Public transport; Quality (philosophy); Survey data collection; Business; Computer science; Marketing; Psychology; Engineering; Statistics; Mathematics","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":[0.000877151,0.0005169001,0.0003925573,0.0008961107,0.0004448841,0.001534949,0.0009744476,0.001340291,0.01771924],"category_scores_gemma":[0.003817159,0.0002519329,0.0009936104,0.000927929,0.0005935133,0.001223805,0.0008006514,0.001113522,0.001532162],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001725919,"about_ca_system_score_gemma":0.001397612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03713942,"about_ca_topic_score_gemma":0.02029463,"domain_scores_codex":[0.9996232,0.0001494156,0.00001585255,0.00009328535,0.00003949551,0.00007882866],"domain_scores_gemma":[0.9984418,0.001029646,0.0002030918,0.00005957409,0.0001623488,0.0001036275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006060473,0.001341153,0.4889434,0.0003579286,0.0006313656,0.00158289,0.01027001,0.1813036,0.001693147,0.2202087,0.02524086,0.06782094],"study_design_scores_gemma":[0.0001387003,0.0002573835,0.06345414,0.00008354887,0.0001689208,0.000361296,0.003282796,0.8768683,0.0001452152,0.04691776,0.008266548,0.00005537188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8118079,0.000798329,0.1237229,0.01543197,0.0002171143,0.0004511047,0.007444318,0.0006565313,0.03946988],"genre_scores_gemma":[0.9830321,0.0002378131,0.006056845,0.0002185541,0.00004220241,0.0002838189,0.0009392272,0.00002362014,0.009165907],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03713942,"threshold_uncertainty_score":0.07384646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.180254068152481,"score_gpt":0.4527319997850413,"score_spread":0.2724779316325602,"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."}}