{"id":"W2746198628","doi":"","title":"需要不確実性の下での空港施設のための容量投資モデル【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":[0.0003498511,0.000234819,0.0002619287,0.0005081376,0.00101666,0.0009345053,0.0005748032,0.000412213,0.0084163],"category_scores_gemma":[0.0008124707,0.0001624442,0.0002059768,0.0004062465,0.000527721,0.0007463888,0.000646462,0.0005466806,0.003408557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007497479,"about_ca_system_score_gemma":0.0007684412,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002184934,"about_ca_topic_score_gemma":0.002613706,"domain_scores_codex":[0.9996665,0.00003629796,0.00002451994,0.0000527672,0.0001684141,0.00005157942],"domain_scores_gemma":[0.9995746,0.00006397312,0.00005313633,0.00005327871,0.0002209041,0.00003411923],"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":[0.001192969,0.0003507689,0.02116815,0.0007090864,0.0001274592,0.002208834,0.002392144,0.003126458,0.5364001,0.0490934,0.03092419,0.3523065],"study_design_scores_gemma":[0.00005150761,0.0005084182,0.01641601,0.0001863234,0.0002042243,0.002914928,0.001877251,0.00993362,0.6435624,0.007016305,0.3172241,0.0001048969],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5456548,0.007250436,0.0870027,0.002726098,0.002313443,0.0004743622,0.001275971,0.001434123,0.3518681],"genre_scores_gemma":[0.8884024,0.003322967,0.02450257,0.0006462521,0.0003771598,0.0004410757,0.0006776114,0.0001433679,0.08148669],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0084163,"threshold_uncertainty_score":0.02815533,"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."}}