{"id":"W3136074968","doi":"10.1155/2021/6679008","title":"Simultaneous Optimization of Train Timetabling and Platforming Problems for High-Speed Multiline Railway Network","year":2021,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fundamental Research Funds for Central Universities of the Central South University; Fundamental Research Funds for the Central Universities","keywords":"Train; Track (disk drive); Integer programming; Computer science; Set (abstract data type); Resource (disambiguation); Resource allocation; Operations research; Engineering; Mathematical optimization; Transport engineering; Algorithm; Computer network; 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":[0.0001981038,0.0001056511,0.0002904243,0.00007001062,0.0000410741,0.0000112741,0.00004036603,0.00006013478,0.000006379392],"category_scores_gemma":[0.00004483137,0.0001003205,0.00006791751,0.000194594,0.00001225217,0.0002903418,6.936153e-7,0.00008174766,5.241101e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001878541,"about_ca_system_score_gemma":0.00002341979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002613054,"about_ca_topic_score_gemma":0.0000281143,"domain_scores_codex":[0.9989676,0.000007590706,0.0006579086,0.0000874582,0.000138418,0.0001410654],"domain_scores_gemma":[0.9992363,0.0001399878,0.0002422387,0.00005559158,0.0002775025,0.00004837506],"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":[0.00004672921,0.00001990093,0.00002908279,0.0001871843,0.00004177458,0.000009672277,0.0007335178,0.9473671,0.03585586,0.0001127418,0.000002649308,0.01559373],"study_design_scores_gemma":[0.002458399,0.0001884477,0.000931228,0.0004171811,0.0001002162,0.00003435439,0.0005076951,0.9811672,0.01312316,0.0002341899,0.0006476704,0.0001902619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5003321,0.001351771,0.4978127,0.00001118333,0.0003443615,0.0001072461,0.00001016857,0.00001779116,0.00001266204],"genre_scores_gemma":[0.8724652,0.0003220896,0.126995,0.000003882041,0.0001266297,0.000002094587,0.00004073692,0.00002245805,0.00002186303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3721331,"threshold_uncertainty_score":0.409095,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007219839826094196,"score_gpt":0.2096770929239005,"score_spread":0.2024572530978063,"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."}}