{"id":"W2742809830","doi":"","title":"ネットワークフロー感度の推定を用いた反復予測交通制御のための二重制御アプローチ【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; Engineering; Aerospace 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":[0.0003207885,0.0002247003,0.000216908,0.0005288215,0.001064622,0.001028041,0.0005014048,0.0004153985,0.009935086],"category_scores_gemma":[0.0006970668,0.0001623649,0.000180941,0.000420785,0.0006237996,0.0008086325,0.0005872773,0.0005395554,0.00375141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007973743,"about_ca_system_score_gemma":0.0007114659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002080716,"about_ca_topic_score_gemma":0.00226383,"domain_scores_codex":[0.999711,0.00002774241,0.00001770108,0.00004858078,0.0001505823,0.00004424153],"domain_scores_gemma":[0.999629,0.00005610041,0.00004412119,0.00004639148,0.0001947901,0.00002954666],"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":[0.000851612,0.0002618512,0.01447906,0.0006358259,0.00008463408,0.001623161,0.00250677,0.003203124,0.5486984,0.07441456,0.02884121,0.3243998],"study_design_scores_gemma":[0.00003887489,0.0003415161,0.01332552,0.000147579,0.0001245301,0.001848468,0.001948415,0.008965595,0.6479926,0.008396934,0.3167798,0.00009017486],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4544334,0.00568837,0.07210126,0.002367528,0.002023394,0.0004178031,0.0009934895,0.001221492,0.4607532],"genre_scores_gemma":[0.8724312,0.002812429,0.0231992,0.000535227,0.0003340976,0.0003522782,0.0005462445,0.0001390672,0.09965035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009935086,"threshold_uncertainty_score":0.03323615,"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."}}