{"id":"W1933586805","doi":"10.1002/atr.1270","title":"Investigating the impact of stochastic vehicle arrivals to optimal stop spacing and headway for a feeder bus route","year":2014,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Headway; Transit (satellite); Transport engineering; Service (business); Travel time; Key (lock); Transit system; Variance (accounting); Engineering; Operations research; Computer science; Simulation; Public transport; Computer security; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001081389,0.000506699,0.0004042887,0.000386486,0.0003055297,0.0008909366,0.0004723667,0.0004996388,0.001482411],"category_scores_gemma":[0.005034405,0.0004412161,0.0005489018,0.00040422,0.0004644775,0.0005208806,0.0004770765,0.0007514094,0.00006071153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001444268,"about_ca_system_score_gemma":0.00182817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03956394,"about_ca_topic_score_gemma":0.03648109,"domain_scores_codex":[0.9995994,0.0001777602,0.00001267713,0.00004506603,0.00005768604,0.0001074977],"domain_scores_gemma":[0.9960386,0.00296019,0.0005505065,0.0000724889,0.0002600625,0.0001182223],"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":[0.00006817915,0.00003477389,0.003181727,0.00001701757,0.00002079513,0.00005160326,0.00001346752,0.993513,0.0007557073,0.000870874,0.0001056698,0.001367299],"study_design_scores_gemma":[0.000007134793,0.0001082865,0.002175824,0.000002247301,0.00001916601,0.000008592114,0.00004323987,0.9969078,0.0003677224,0.0003014212,0.0000534578,0.000005157779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9762755,0.00008113824,0.02098331,0.0001158834,0.00001519213,0.00002598466,0.00007817393,0.00002603278,0.002398712],"genre_scores_gemma":[0.9966925,0.00004585206,0.002869043,0.000007919962,0.000003204247,0.000009394698,0.0000297343,0.00000575159,0.0003366004],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03956394,"threshold_uncertainty_score":0.07866734,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01769057919546066,"score_gpt":0.3213689490401666,"score_spread":0.3036783698447059,"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."}}