{"id":"W2619343860","doi":"10.1155/2017/8426926","title":"Air Transport versus High-Speed Rail: An Overview and Research Agenda","year":2017,"lang":"en","type":"article","venue":"Journal of Advanced Transportation","topic":"Aviation Industry Analysis and Trends","field":"Economics, Econometrics and Finance","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Natural Science Foundation of China","keywords":"Competition (biology); Transport engineering; Resilience (materials science); Air transport; Multimodal transport; Regional science; Computer science; Psychological resilience; Distribution (mathematics); Range (aeronautics); Economic geography; Operations research; Engineering; Geography","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":[0.0009434779,0.0001088681,0.0003747226,0.0002717115,0.0003618729,0.0000552516,0.0002384274,0.00009895227,0.0001994246],"category_scores_gemma":[0.00005490835,0.0001144828,0.000130769,0.0001460522,0.00008764157,0.001518869,0.000002571902,0.0003262939,0.00001077323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004553901,"about_ca_system_score_gemma":0.00002963941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001090003,"about_ca_topic_score_gemma":0.0002232027,"domain_scores_codex":[0.9986483,0.00001989522,0.0007981203,0.000219247,0.0001327151,0.0001816869],"domain_scores_gemma":[0.9983363,0.00003964332,0.001011538,0.0002885349,0.000199383,0.0001246568],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002854632,0.000853342,0.4460884,0.0002461813,0.000989465,0.0003567124,0.00861453,0.03911995,0.0008466836,0.4402953,0.0003959041,0.0593389],"study_design_scores_gemma":[0.002464202,0.0003011516,0.9753662,0.00003469162,0.00003755689,0.000002449231,0.00029442,0.00004802895,0.0001482539,0.008787441,0.01238117,0.0001343834],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954503,0.001557699,0.0005208561,0.001027804,0.0004854405,0.00006453196,0.00008400256,0.000007027536,0.0008023726],"genre_scores_gemma":[0.9965664,0.001825216,0.001117259,0.00002956882,0.0001788614,0.000001861684,0.00004378289,0.00001527224,0.0002217723],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5292779,"threshold_uncertainty_score":0.4668474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1850705754406438,"score_gpt":0.3757670131103422,"score_spread":0.1906964376696983,"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."}}