{"id":"W2749961546","doi":"","title":"路側に沿った自転車の影響を受けた電動車両流のためのセルラオートマトン(CA)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":"Aerospace engineering; Computer science; Aeronautics; 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":[0.0001535715,0.000203427,0.0001855317,0.0004718591,0.0009940923,0.0008745015,0.0005497885,0.0004095075,0.008910693],"category_scores_gemma":[0.0004274199,0.000141425,0.000179561,0.0004413497,0.0005067977,0.0007681872,0.0004783554,0.0004683832,0.002571657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007790379,"about_ca_system_score_gemma":0.0005842906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003615373,"about_ca_topic_score_gemma":0.004258787,"domain_scores_codex":[0.9998176,0.00001052974,0.000009025342,0.00004551193,0.00007964521,0.00003773129],"domain_scores_gemma":[0.9997832,0.00002672716,0.00002982159,0.00003101014,0.0001076612,0.00002167013],"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":[0.0006962363,0.0001632097,0.01072671,0.0005397949,0.00006245267,0.001321691,0.001317433,0.001979199,0.7605882,0.05933479,0.02002366,0.1432466],"study_design_scores_gemma":[0.00002501529,0.0001897508,0.009743543,0.00007556356,0.00008717442,0.001276341,0.0009716151,0.008917399,0.774947,0.003814175,0.1998893,0.00006304938],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6551874,0.004417941,0.03470366,0.001411717,0.001470324,0.0002466512,0.001002723,0.001019708,0.3005399],"genre_scores_gemma":[0.9212183,0.001341309,0.01253578,0.000287361,0.0001635307,0.0001552876,0.0003687773,0.00008552813,0.06384412],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008910693,"threshold_uncertainty_score":0.02980924,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004795749399400602,"score_gpt":0.2137466256821652,"score_spread":0.2089508762827646,"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."}}