{"id":"W7016690429","doi":"","title":"最新デバイスの耐放射線性強化技術に関する検討委員会: 平成21年度成果報告書","year":2011,"lang":"ja","type":"report","venue":"JAXA Repository (JAXA)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Los Alamos National Laboratory; Sandia National Laboratories; Lawrence Livermore National Laboratory; University of Illinois at Urbana-Champaign; Defense Advanced Research Projects Agency; VMware; Japan Aerospace Exploration Agency; U.S. Department of Defense; California Institute of Technology; Intel Corporation; Coastal Carolina University; University of Toronto; Carnegie Mellon University; Microsoft Research; University of Southern California; Cisco Systems; University of Pennsylvania; Princeton University; National Science Foundation","keywords":"","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":["metaepi_narrow","sts","research_integrity","insufficient_payload"],"category_scores_codex":[0.006172133,0.007033734,0.008010752,0.003429222,0.003143326,0.001882881,0.006300432,0.008574308,0.004596017],"category_scores_gemma":[0.002025282,0.007634664,0.005510776,0.003162807,0.002822106,0.002006299,0.002993473,0.009130817,0.08346873],"about_ca_system_candidate":true,"about_ca_system_consensus":true,"about_ca_system_score_codex":0.008735266,"about_ca_system_score_gemma":0.0122601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005895804,"about_ca_topic_score_gemma":0.0003055241,"domain_scores_codex":[0.9628266,0.003248524,0.00901646,0.008890016,0.009629385,0.006389081],"domain_scores_gemma":[0.963793,0.0009421293,0.0129093,0.013142,0.005383186,0.003830428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001934844,0.005214121,0.03132951,0.00550228,0.008899314,0.03149057,0.004852214,0.00005313574,0.05211305,0.0004001901,0.8452302,0.01298063],"study_design_scores_gemma":[0.002964628,0.001307798,0.01601382,0.00420144,0.005858277,0.01746173,0.0006582217,0.0001941623,0.02699276,0.0001748339,0.916038,0.008134293],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03240993,0.03300204,0.00006324273,0.00009784949,0.05071026,0.00706854,0.001268416,0.003851088,0.8715286],"genre_scores_gemma":[0.2033699,0.005257277,0.00239656,0.0004152283,0.03046142,0.002565989,0.001976052,0.006723495,0.7468341],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.17096,"threshold_uncertainty_score":0.9998916,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05273802188759197,"score_gpt":0.2711517947231308,"score_spread":0.2184137728355389,"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."}}