{"id":"W656994265","doi":"","title":"A Quarter of Century of National Road Map Database in Japan and Challenging for Contribution to Advanced ITS","year":2013,"lang":"en","type":"article","venue":"20th ITS World CongressITS Japan","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Road map; General partnership; Quarter (Canadian coin); Database; Transport engineering; Service (business); Public–private partnership; Computer science; Business; Engineering; Geography; Cartography; Finance; Marketing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0104316,0.0005353963,0.001045096,0.002625919,0.002003932,0.006750807,0.002655589,0.001416423,0.01081543],"category_scores_gemma":[0.01709181,0.0006545291,0.0005125448,0.005913227,0.001478971,0.01647173,0.004120623,0.003454997,0.005048982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002427695,"about_ca_system_score_gemma":0.005996747,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01437376,"about_ca_topic_score_gemma":0.008068805,"domain_scores_codex":[0.99383,0.001298559,0.0009143561,0.001189693,0.002322279,0.0004450266],"domain_scores_gemma":[0.9762759,0.001712252,0.0006876538,0.005976796,0.01325537,0.002092017],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003436422,0.0001060843,0.00672514,0.0004693308,0.00006868951,0.0005616472,0.002135391,0.001000559,0.004658842,0.09435759,0.3482543,0.5413188],"study_design_scores_gemma":[0.00002106881,0.00006535513,0.003073827,0.0002327365,0.00004978665,0.000535179,0.001505923,0.004344234,0.002216018,0.01204449,0.9758563,0.00005516169],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07137714,0.06463778,0.5270308,0.1633139,0.03228037,0.0006432995,0.00826454,0.009493435,0.1229588],"genre_scores_gemma":[0.3242102,0.05386033,0.4236229,0.01806315,0.01396946,0.0007330535,0.02217656,0.004140165,0.1392241],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01437376,"threshold_uncertainty_score":0.05516827,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009518124695624273,"score_gpt":0.240520650902475,"score_spread":0.2310025262068507,"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."}}