{"id":"W2048138820","doi":"10.1109/tits.2014.2310771","title":"Challenges Toward Wireless Communications for High-Speed Railway","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Power Line Communications and Noise","field":"Engineering","cited_by":486,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Fundamental Research Funds for the Central Universities; State Key Laboratory of Rail Traffic Control and Safety; National Natural Science Foundation of China","keywords":"Wireless; Engineering; Key (lock); Maglev; Channel (broadcasting); Telecommunications; Computer science; Computer network; Computer security; Electrical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003514112,0.0002765886,0.0003464449,0.000252937,0.000231796,0.0000536225,0.0006099987,0.0001610705,0.00002620649],"category_scores_gemma":[0.000003190059,0.0002925851,0.0001834747,0.0002274734,0.00007045412,0.0001773863,4.79138e-7,0.0002663874,0.00008601377],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008671348,"about_ca_system_score_gemma":0.00001936491,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008464644,"about_ca_topic_score_gemma":0.0003878354,"domain_scores_codex":[0.9984422,0.00009361649,0.0007081183,0.0002662769,0.000213801,0.0002759425],"domain_scores_gemma":[0.9979562,0.0004083776,0.00008424582,0.001223103,0.0001972739,0.0001308315],"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":[0.0001518659,0.0008588235,0.00002595229,0.001164092,0.0006948689,0.000001004403,0.008110476,0.7296162,0.006245877,0.081906,0.0009517428,0.1702731],"study_design_scores_gemma":[0.002757511,0.00063563,0.000949386,0.0008402675,0.0004977363,0.0000109668,0.003950668,0.7065296,0.08997723,0.001157037,0.190706,0.001987965],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008441977,0.001247415,0.9852581,0.0004442445,0.001630624,0.0008358242,0.0002512964,0.0006533454,0.001237158],"genre_scores_gemma":[0.9929402,0.004669793,0.001279444,0.00002999854,0.00007139246,0.0006155721,0.0001402203,0.00008165002,0.0001717244],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9844982,"threshold_uncertainty_score":0.9999526,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06447772942940215,"score_gpt":0.2753646333383552,"score_spread":0.210886903908953,"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."}}