{"id":"W2014096215","doi":"10.5267/j.msl.2011.12.012","title":"A hybrid method to solve railroad passenger scheduling problem","year":2012,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Scheduling (production processes); Operations research; Mathematical optimization; Mathematics","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":[0.001465212,0.0001823179,0.0001471535,0.0003812228,0.0001992628,0.0001565389,0.0004993764,0.00001671331,0.00002709619],"category_scores_gemma":[0.000007710282,0.0001682279,0.0000515669,0.000778511,0.00006320882,0.0005649993,0.0001443155,0.00009538355,0.0002852153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001409112,"about_ca_system_score_gemma":0.000002688518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002195615,"about_ca_topic_score_gemma":8.621368e-7,"domain_scores_codex":[0.9980156,0.00001398964,0.000226379,0.0003213528,0.0005057274,0.0009169731],"domain_scores_gemma":[0.9993497,0.00001581268,0.0000268716,0.0003565382,0.00001031797,0.0002408214],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002353967,0.00003930838,0.0007174925,0.0001435477,0.0000428193,0.00001753013,0.001053344,0.803823,0.1354326,0.01335981,0.009674617,0.03569356],"study_design_scores_gemma":[0.001108647,0.00009204593,0.02584733,0.0004210462,0.0001254355,0.00006312215,0.001603251,0.3164716,0.06288039,0.0002800404,0.5880748,0.003032326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2205915,0.00005618194,0.745917,0.00148038,0.001025614,0.0003440054,8.067278e-7,0.0003673729,0.03021708],"genre_scores_gemma":[0.7650658,0.000002874653,0.2328506,0.001641425,0.0001794885,0.00007816229,7.393986e-7,0.00002404584,0.0001569258],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5784002,"threshold_uncertainty_score":0.6860136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009380607581404207,"score_gpt":0.2338835022972147,"score_spread":0.2245028947158105,"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."}}