{"id":"W2753837729","doi":"","title":"財政的に持続可能な鉄道サービスと都市開発【Powered by NICT】","year":2016,"lang":"ja","type":"article","venue":"Journal of Advanced Transportation","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Aeronautics; Aerospace engineering; Computer science; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001645671,0.000227084,0.0002274464,0.0004148411,0.0008248251,0.0008464439,0.0005373222,0.0003880853,0.008898615],"category_scores_gemma":[0.000436733,0.0001401133,0.0001929227,0.000365101,0.0004456218,0.0007805995,0.0005746991,0.0005101286,0.003305514],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000741543,"about_ca_system_score_gemma":0.0005187513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001261941,"about_ca_topic_score_gemma":0.001556399,"domain_scores_codex":[0.9998071,0.00001464152,0.000008980995,0.00003647703,0.00009292325,0.00003993745],"domain_scores_gemma":[0.999797,0.00002728355,0.0000276662,0.00002902353,0.00009817427,0.00002082145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005830077,0.0001723279,0.007564554,0.0006498229,0.00006383342,0.001456899,0.001102247,0.002411148,0.7118804,0.07046363,0.02890009,0.174752],"study_design_scores_gemma":[0.00002272835,0.0001993381,0.005173816,0.0001008219,0.00008126684,0.00151355,0.000733674,0.01214416,0.7181144,0.004541455,0.2573142,0.00006064766],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5125273,0.00729844,0.05776547,0.003036287,0.002608071,0.0002830556,0.00120665,0.001686391,0.4135884],"genre_scores_gemma":[0.9094986,0.001969804,0.01307788,0.0005612261,0.0003008674,0.0002171701,0.0004713588,0.0001212131,0.07378179],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008898615,"threshold_uncertainty_score":0.02976882,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004916072688546676,"score_gpt":0.2133579776355112,"score_spread":0.2084419049469645,"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."}}