{"id":"W2749746357","doi":"","title":"公共輸送運転管理における時間を定めた乗換え協調のための移動需要予測【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","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":[0.0003293919,0.0002444173,0.0001987235,0.0006761927,0.001132795,0.001230372,0.0004548242,0.000390938,0.0095559],"category_scores_gemma":[0.0007438117,0.0001609459,0.0001815771,0.0005165558,0.0007978167,0.0007838192,0.0005490308,0.0005198769,0.003131318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001032259,"about_ca_system_score_gemma":0.0009602458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00307879,"about_ca_topic_score_gemma":0.003048435,"domain_scores_codex":[0.9996876,0.00003254591,0.0000198912,0.00004912285,0.0001621383,0.00004868074],"domain_scores_gemma":[0.9995118,0.00007159214,0.00005682281,0.00005087034,0.0002745559,0.00003436372],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006543603,0.0002750814,0.02482434,0.0007452859,0.0001029059,0.001914019,0.003625677,0.004685746,0.3833905,0.1312477,0.02758159,0.4209527],"study_design_scores_gemma":[0.00003943533,0.0003658195,0.03073497,0.0002082803,0.0001799841,0.002734609,0.003877565,0.0126096,0.5394157,0.02083653,0.3888711,0.0001265126],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3886621,0.004617642,0.056624,0.001935002,0.001189671,0.0003090185,0.0007410794,0.0007185567,0.5452029],"genre_scores_gemma":[0.8933713,0.002608761,0.01767865,0.0003522588,0.0002919189,0.0002607405,0.0004622417,0.00009424808,0.08487985],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0095559,"threshold_uncertainty_score":0.0319677,"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."}}