{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002613,0.0003568362,0.0005604205,0.0002502573,0.00008459677,0.00001571387,0.0003331951,0.000376627,0.000474606],"category_scores_gemma":[0.00005324022,0.0002762944,0.0002856338,0.0002617273,0.0001434175,0.001259441,0.000002497803,0.0005001356,0.00005138905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001310589,"about_ca_system_score_gemma":0.00007388029,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005804505,"about_ca_topic_score_gemma":0.00005737093,"domain_scores_codex":[0.9977118,0.00004070864,0.001218773,0.000238714,0.0003693079,0.0004206438],"domain_scores_gemma":[0.9986904,0.0001534691,0.00046563,0.0002688928,0.000259393,0.0001621797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001974819,0.0005152473,0.003273435,0.0006433142,0.001341754,0.0005591154,0.006141481,0.02817919,0.8113381,0.01723401,0.01161003,0.1171895],"study_design_scores_gemma":[0.04084649,0.008802131,0.3349435,0.008122174,0.002494818,0.0004610637,0.02066131,0.0003357453,0.1796312,0.1516841,0.2465187,0.005498747],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9526321,0.01889552,0.02136874,0.001677797,0.002521927,0.0002684218,0.000371224,0.0001587917,0.002105508],"genre_scores_gemma":[0.9855066,0.01049549,0.003279843,0.00003192657,0.0001604749,0.000005045671,0.00002904555,0.00005126446,0.0004403313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6317069,"threshold_uncertainty_score":0.9999689,"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."}}