{"id":"W2752958960","doi":"","title":"特性評価,測定および輸送サービス品質の管理【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; Environmental science","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":[0.0001867204,0.0002314409,0.0002237513,0.0004308642,0.0008797614,0.000864834,0.0005242844,0.0004040863,0.007283477],"category_scores_gemma":[0.0005071217,0.0001535032,0.0001956917,0.0003679454,0.0005120229,0.0007872558,0.0006073904,0.000509712,0.002608414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006654517,"about_ca_system_score_gemma":0.0005509069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001376507,"about_ca_topic_score_gemma":0.001818067,"domain_scores_codex":[0.9997959,0.00001631636,0.00001119442,0.00003533214,0.0001036364,0.00003758298],"domain_scores_gemma":[0.9997974,0.00002855384,0.0000303442,0.00002940725,0.00009423359,0.00001997993],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007378485,0.0001953407,0.009782341,0.0007010015,0.0000758144,0.001921593,0.00137525,0.003016721,0.6493811,0.06828785,0.02631695,0.2382083],"study_design_scores_gemma":[0.00002825886,0.000276734,0.006716541,0.0001124677,0.0001114015,0.002144176,0.0008918433,0.01473486,0.7032642,0.00587237,0.2657683,0.00007880812],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5264038,0.008281955,0.08254549,0.0029304,0.002735286,0.0003583548,0.001005621,0.001748873,0.3739901],"genre_scores_gemma":[0.909561,0.002279591,0.01840526,0.0005106277,0.0002940584,0.0002210126,0.0003885583,0.0001105367,0.06822941],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007283477,"threshold_uncertainty_score":0.02436566,"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."}}