{"id":"W2745321750","doi":"","title":"情報ベースの避難作業のための統合フレームワークのオンラインキャリブレーション【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; Engineering; Aerospace engineering; Computer 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":[0.0003036052,0.0002419487,0.0002887674,0.0004176337,0.0008327382,0.0007582761,0.0005899745,0.0003866942,0.007379763],"category_scores_gemma":[0.0008287043,0.0001302083,0.0002253852,0.000366091,0.0004038625,0.0006027136,0.000662844,0.0004919174,0.002901538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005714785,"about_ca_system_score_gemma":0.0007357316,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001709791,"about_ca_topic_score_gemma":0.00199898,"domain_scores_codex":[0.9996907,0.00003688959,0.0000257046,0.00004519855,0.0001469525,0.00005464828],"domain_scores_gemma":[0.9996463,0.00005672156,0.00004840182,0.00004790183,0.0001692783,0.00003137952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001731763,0.0004288453,0.02493932,0.0008389399,0.0001550585,0.003453178,0.001960727,0.002428311,0.4216115,0.02682232,0.03601345,0.4796166],"study_design_scores_gemma":[0.00008824906,0.001037049,0.02180632,0.0002883209,0.0003346359,0.007701464,0.001721133,0.01144615,0.5642568,0.005609297,0.3855786,0.0001319364],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6574217,0.009175601,0.09198351,0.003324745,0.003403375,0.0005559258,0.001360009,0.002039252,0.2307358],"genre_scores_gemma":[0.9117547,0.003704942,0.02434136,0.0008836678,0.0005335767,0.0005831671,0.0006358253,0.0001535,0.05740927],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007379763,"threshold_uncertainty_score":0.02468777,"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."}}