{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002354771,0.0003137209,0.0005043187,0.000222518,0.00007119664,0.00001420963,0.0003048305,0.0003348606,0.0003193692],"category_scores_gemma":[0.00004564366,0.0002389345,0.0002561736,0.0002465856,0.0001300869,0.001164171,0.000002037139,0.0004288138,0.0000310346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000114791,"about_ca_system_score_gemma":0.00006451784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003914897,"about_ca_topic_score_gemma":0.00003714049,"domain_scores_codex":[0.9979209,0.00003483618,0.001124947,0.000206396,0.0003364513,0.0003764838],"domain_scores_gemma":[0.9988192,0.0001326601,0.000430154,0.0002415115,0.0002326393,0.0001438003],"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":[0.00157848,0.0004154696,0.002561228,0.0005502458,0.001115092,0.0004660714,0.005847376,0.02630969,0.8000461,0.0164757,0.01018547,0.134449],"study_design_scores_gemma":[0.04010585,0.008828357,0.3339767,0.008400791,0.002346195,0.0004758243,0.02005466,0.0002320321,0.2105468,0.1389089,0.2309374,0.005186497],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9502205,0.02097355,0.02187433,0.001834942,0.002601232,0.0002359567,0.0002753117,0.0001676101,0.001816597],"genre_scores_gemma":[0.985116,0.01122382,0.003063681,0.00003100563,0.0001499811,0.000003662315,0.00001766492,0.00004599618,0.0003482006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5894994,"threshold_uncertainty_score":0.9743468,"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."}}