{"id":"W637711567","doi":"","title":"Enhanced Customer Service Key to Improving Transit Systems","year":2008,"lang":"en","type":"article","venue":"Metrologia","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Workflow; Customer relationship management; Computer science; Service (business); Business; Telecommunications; Marketing; Database","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":[],"consensus_categories":[],"category_scores_codex":[0.0003205067,0.00007041367,0.0001197162,0.00009542151,0.0003859218,0.00002681496,0.0001382757,0.00009202647,0.00006595848],"category_scores_gemma":[0.00006687576,0.00006761305,0.00002709158,0.0005858022,0.00003368706,0.0001224718,0.000002943774,0.00007443459,0.0002315764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003948731,"about_ca_system_score_gemma":0.00007188514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00346254,"about_ca_topic_score_gemma":0.0009704625,"domain_scores_codex":[0.9991302,0.00008914206,0.0001498498,0.0001708489,0.0002331182,0.0002267774],"domain_scores_gemma":[0.9995782,0.00005362162,0.00004733636,0.00008898631,0.0001345478,0.00009726712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0003662482,0.0002384284,0.05641275,0.0001470228,0.0001257681,0.00008663332,0.2729715,0.6011444,0.03348489,0.02094597,0.007465035,0.006611336],"study_design_scores_gemma":[0.004915934,0.0007412455,0.5626802,0.0001635686,0.0003341049,0.00001933099,0.04344533,0.01709398,0.01014978,0.0001001085,0.3572042,0.003152225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8523296,0.0000800265,0.1223943,0.0009273029,0.0005595377,0.0002634155,0.000008640412,0.0003091807,0.02312802],"genre_scores_gemma":[0.9957824,0.00001334327,0.002014201,0.0005950368,0.00009851951,0.00002193611,0.00001086531,0.000007225613,0.001456472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5840504,"threshold_uncertainty_score":0.5234348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02588501626433017,"score_gpt":0.2687484322246362,"score_spread":0.242863415960306,"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."}}