{"id":"W4412582898","doi":"10.1016/j.icheatmasstransfer.2025.109400","title":"Temperature distribution and freezing range of a railway tunnel in cold regions under high-speed train piston effect","year":2025,"lang":"en","type":"article","venue":"International Communications in Heat and Mass Transfer","topic":"Aerodynamics and Fluid Dynamics Research","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Guangdong Provincial Key Laboratory of Modern Civil Engineering Technology, South China University of Technology; State Key Laboratory of Subtropical Building Science; Basic and Applied Basic Research Foundation of Guangdong Province; State Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering; Chongqing Jiaotong University; National Natural Science Foundation of China","keywords":"Piston (optics); Mechanics; Range (aeronautics); Materials science; Environmental science; Optics; Physics; Composite material","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001505497,0.0002011622,0.0002824593,0.0004235556,0.0006729577,0.0002899178,0.0003471838,0.0003279471,0.001693506],"category_scores_gemma":[0.0001966282,0.0001460545,0.0003409118,0.0002729386,0.0006047051,0.0003396533,0.0002504357,0.0003605966,0.0001090264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002596467,"about_ca_system_score_gemma":0.0002389854,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005578592,"about_ca_topic_score_gemma":0.003640318,"domain_scores_codex":[0.9999336,0.000005355982,0.00000191673,0.00001867194,0.00001434654,0.00002614395],"domain_scores_gemma":[0.9997389,0.0000737908,0.00003769534,0.00001951592,0.00006760687,0.00006257983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.008162939,0.0007277582,0.1953813,0.0001868193,0.0001653876,0.004438769,0.001950938,0.06663218,0.7085305,0.001232307,0.002172783,0.01041827],"study_design_scores_gemma":[0.0001015785,0.001429944,0.7624205,0.00003391684,0.0001323575,0.0009611357,0.002076848,0.1131814,0.1180464,0.0006104563,0.0008450157,0.0001604455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991193,0.00002487875,0.0002536055,0.00001450031,0.000004724041,0.000001930595,0.00008858765,0.00001863883,0.00047378],"genre_scores_gemma":[0.9997079,0.000009039546,0.00004576196,0.000002503151,0.000001487263,0.000001200635,0.00006252855,0.000002514013,0.0001670366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005578592,"threshold_uncertainty_score":0.01109219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01234630058780267,"score_gpt":0.2714005569960612,"score_spread":0.2590542564082586,"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."}}