{"id":"W2998971297","doi":"10.1155/2020/5081315","title":"Improving Synchronization in an Air and High-Speed Rail Integration Service via Adjusting a Rail Timetable: A Real-World Case Study in China","year":2020,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Railway Systems and Energy Efficiency","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Higher Education Discipline Innovation Project; Beijing Jiaotong University; National Natural Science Foundation of China","keywords":"Synchronization (alternating current); Subnetwork; Transport engineering; Service (business); Transfer (computing); Transfer station; Focus (optics); Rail network; China; Operations research; Computer science; Engineering; Computer network; Business","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":[0.0002826229,0.0001536572,0.0002966185,0.0002764422,0.0000412957,0.00002488583,0.00006326809,0.00004723273,0.000004412141],"category_scores_gemma":[0.00002031584,0.0001498219,0.00002293622,0.0009164573,0.000006174841,0.001136074,0.000001449793,0.0002481989,2.739547e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001033051,"about_ca_system_score_gemma":0.00003236918,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002392987,"about_ca_topic_score_gemma":0.0352622,"domain_scores_codex":[0.9986961,0.00004990679,0.0007652356,0.000160425,0.0001764823,0.00015186],"domain_scores_gemma":[0.9994678,0.00002626717,0.0002335194,0.00006960614,0.0001137671,0.00008900931],"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":[0.00006411508,0.00006282406,0.009980759,0.0001564445,0.000009123339,0.0004632843,0.01702361,0.9217446,0.02233457,0.000007503583,3.6244e-7,0.02815282],"study_design_scores_gemma":[0.002863747,0.000414998,0.3241579,0.0002153618,0.00005247309,0.00007713898,0.009989908,0.6609997,0.0009786437,0.00001534645,0.000004906099,0.0002298459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9681002,0.0001268277,0.03127741,0.00004945074,0.0001582629,0.0002304098,0.000002548331,0.00004175559,0.00001306143],"genre_scores_gemma":[0.9976772,0.00003437661,0.002123851,0.00001855894,0.00009260177,0.000005118477,0.00001752069,0.00002860457,0.000002182395],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3141771,"threshold_uncertainty_score":0.9823418,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008266838730882303,"score_gpt":0.2261389514664262,"score_spread":0.2178721127355439,"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."}}