{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006988032,0.00008259762,0.0001876209,0.00008861788,0.0002316714,0.00002924439,0.00008045315,0.00004199366,0.000003799],"category_scores_gemma":[0.0002832102,0.00006209122,0.00009179498,0.0002092426,0.0000712515,0.0003571226,5.757735e-7,0.00009037217,1.588908e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003570326,"about_ca_system_score_gemma":0.0001170325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001683592,"about_ca_topic_score_gemma":0.0002296758,"domain_scores_codex":[0.9990446,0.00005342262,0.0004139981,0.00009194018,0.0002482038,0.0001478599],"domain_scores_gemma":[0.9987505,0.0002944408,0.0004406546,0.00005156108,0.000344026,0.0001187936],"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":[0.00009439213,0.00001320897,0.004024636,0.00001410455,0.00002162014,2.670426e-7,0.04816844,0.9403679,0.00380358,0.0008130539,0.00001338808,0.002665419],"study_design_scores_gemma":[0.002951645,0.001287222,0.9535593,0.0005329319,0.0002036269,0.000003634793,0.02589371,0.01093464,0.00116652,0.002891106,0.0002601668,0.0003155199],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7553505,0.00003750716,0.2438219,0.0004805739,0.00008332885,0.0001876136,0.00001340643,0.00000854802,0.00001666876],"genre_scores_gemma":[0.9716575,0.000008366706,0.02815118,0.00004302173,0.0000995747,0.000005253936,0.00001031203,0.000009862562,0.00001499594],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9495347,"threshold_uncertainty_score":0.2532006,"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."}}