{"id":"W2749424827","doi":"","title":"時刻,悪天候と交通事故を考慮した高速道路の路線旅行時間分布の推定【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":[0.0002269769,0.0002471483,0.000183368,0.0005802305,0.001216673,0.001337646,0.0004958977,0.000438793,0.0125278],"category_scores_gemma":[0.0005241815,0.0001471216,0.000176205,0.0004360689,0.000814674,0.000978405,0.0006083566,0.0005986026,0.00337107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001214354,"about_ca_system_score_gemma":0.0009500735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002905675,"about_ca_topic_score_gemma":0.003166457,"domain_scores_codex":[0.9997666,0.00001782286,0.00001267197,0.00004005159,0.0001234199,0.00003934024],"domain_scores_gemma":[0.9997268,0.00002952454,0.00003345932,0.0000295139,0.0001542582,0.00002643793],"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":[0.0006141808,0.0002771291,0.01719547,0.0007063231,0.00008258595,0.001700978,0.003096923,0.004327247,0.4196428,0.2079754,0.0389771,0.3054038],"study_design_scores_gemma":[0.00004063507,0.0002946793,0.02011572,0.0001808794,0.0001140703,0.001794553,0.003515391,0.01194971,0.4671055,0.02507621,0.4696937,0.0001189777],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3283301,0.005857653,0.0405904,0.002913681,0.001938308,0.0002603556,0.0007983706,0.0006904019,0.6186208],"genre_scores_gemma":[0.8485125,0.002768825,0.01319559,0.0004154197,0.0003602048,0.0002067557,0.00042151,0.00008917862,0.1340299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0125278,"threshold_uncertainty_score":0.04190964,"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."}}