{"id":"W2749547787","doi":"","title":"降雨条件下での交通流予測のための統合モデル【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; Systems engineering; Aerospace engineering; 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":[0.0003151799,0.0002388382,0.0002745853,0.0004624777,0.0009239902,0.000885084,0.0006457551,0.0004225037,0.007541743],"category_scores_gemma":[0.0008277296,0.00015501,0.0002224747,0.0003905372,0.0005031665,0.0007214452,0.0006804318,0.0005504935,0.003116451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006957,"about_ca_system_score_gemma":0.0007170297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001656387,"about_ca_topic_score_gemma":0.001805718,"domain_scores_codex":[0.9996943,0.00003359265,0.00002224836,0.00005263217,0.000146245,0.00005099874],"domain_scores_gemma":[0.9996293,0.00005875888,0.00004872574,0.0000508767,0.0001815384,0.00003090234],"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":[0.001286517,0.0003281643,0.01660916,0.0007582404,0.0001194646,0.002377311,0.002077102,0.002511581,0.5444691,0.04605807,0.03032897,0.3530763],"study_design_scores_gemma":[0.00005861761,0.000544522,0.01275859,0.0001869242,0.0002091506,0.003526417,0.00142305,0.01052037,0.6555253,0.006607305,0.3085341,0.0001057081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5911008,0.00859327,0.09464137,0.003270485,0.003269303,0.0005323067,0.001227792,0.001881305,0.2954835],"genre_scores_gemma":[0.9049782,0.003167726,0.02540667,0.0007908097,0.0004575736,0.0005145418,0.0005991248,0.0001588243,0.06392658],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007541743,"threshold_uncertainty_score":0.02522963,"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."}}