{"id":"W2745002844","doi":"","title":"動的分割多重都市サブネットワークのためのモデルに基づく需要バランス制御【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; Engineering; Computer science","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":[0.0001398726,0.000224618,0.0002126048,0.0004016868,0.0008588179,0.001078777,0.0006065643,0.0003934231,0.01070967],"category_scores_gemma":[0.0003531293,0.0001458039,0.0001844476,0.0003750088,0.0004937111,0.0008110888,0.0005982912,0.0005120968,0.003485211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007753729,"about_ca_system_score_gemma":0.0004732077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001261296,"about_ca_topic_score_gemma":0.001521695,"domain_scores_codex":[0.9998471,0.00001116141,0.000006822607,0.00003118461,0.00007143287,0.00003233822],"domain_scores_gemma":[0.9998599,0.00001674812,0.00002096633,0.00001845541,0.00006697713,0.00001685202],"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":[0.0004607255,0.0001649737,0.005851471,0.0006565162,0.00006613225,0.001328676,0.001240429,0.004149762,0.6584417,0.1220601,0.02913676,0.1764428],"study_design_scores_gemma":[0.00002841634,0.0002159682,0.006035001,0.0001224133,0.00009218958,0.00132176,0.001229415,0.02250338,0.6370313,0.01037577,0.3209611,0.00008326831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4283011,0.006327853,0.05240085,0.003032731,0.002385696,0.0002386719,0.0009377431,0.001238817,0.5051365],"genre_scores_gemma":[0.8984272,0.001947364,0.01323126,0.0004642612,0.00025704,0.0002106032,0.0004046774,0.0001039891,0.08495347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01070967,"threshold_uncertainty_score":0.0358274,"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."}}