{"id":"W2964514245","doi":"10.1155/2019/1382394","title":"Increasing Robustness by Reallocating the Margins in the Timetable","year":2019,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for the Central Universities","keywords":"Punctuality; Headway; Unavailability; Robustness (evolution); Operations research; Computer science; Heuristic; Engineering; Transport engineering; Simulation; Reliability engineering","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":[0.0005928237,0.00007273971,0.0001274904,0.00004683898,0.00003584334,0.00002009608,0.0001519054,0.00002809185,0.000009153136],"category_scores_gemma":[0.000009685825,0.00004212953,0.00004510222,0.0002272252,0.000008471001,0.000280172,4.820553e-7,0.0001759856,0.000001542792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002862977,"about_ca_system_score_gemma":0.00001221709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000536214,"about_ca_topic_score_gemma":0.00007653598,"domain_scores_codex":[0.9992456,0.0000371555,0.000352699,0.00004970698,0.0001944262,0.0001203662],"domain_scores_gemma":[0.9996359,0.00009439108,0.000116045,0.00009562785,0.00004145122,0.00001657498],"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":[0.00001196845,0.00001033923,0.001519871,0.0000243894,0.0000076544,0.000003058625,0.001476822,0.9810819,0.0138836,0.00009742755,0.0000444539,0.001838511],"study_design_scores_gemma":[0.004322316,0.0003712276,0.7624862,0.001160194,0.0001445944,0.0002490508,0.03018833,0.1626935,0.005419387,0.0002888057,0.03187215,0.0008041901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933752,0.0007105877,0.004762683,0.00008545887,0.000295512,0.00008551808,0.00000156913,0.000009969643,0.0006735326],"genre_scores_gemma":[0.9988762,0.00009558626,0.0009088263,0.00001939396,0.00004837686,0.000002790888,0.000004912274,0.00001196111,0.00003196323],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8183883,"threshold_uncertainty_score":0.1717992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003884217080859319,"score_gpt":0.1917805140580304,"score_spread":0.1878962969771711,"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."}}