{"id":"W7146828806","doi":"","title":"拡張Hensel構成による多変数多項式の近似GCD計算とその安定化 : その1 (数式処理の新たな発展 : その最新研究と基礎理論の再構成)","year":2017,"lang":"ja","type":"article","venue":"Institutional Repositories DataBase (IRDB)","topic":"Military Technology and Strategies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"123 Certification (Canada)","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002759232,0.0003434085,0.0003490724,0.002758455,0.001205388,0.003021538,0.0007036994,0.0005950992,0.01139697],"category_scores_gemma":[0.01058134,0.0004118681,0.0003574104,0.003012591,0.002062583,0.008764158,0.001481224,0.0005562044,0.003740973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009965166,"about_ca_system_score_gemma":0.001914826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003820367,"about_ca_topic_score_gemma":0.004482604,"domain_scores_codex":[0.9977663,0.0004371187,0.0003024779,0.0005968452,0.0007316187,0.0001656824],"domain_scores_gemma":[0.9932105,0.002230445,0.0007142689,0.001192529,0.002280786,0.000371538],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0008411338,0.0001720654,0.03340758,0.0007313904,0.00009916494,0.0008792263,0.003125242,0.001894115,0.009951852,0.3996734,0.0522523,0.4969726],"study_design_scores_gemma":[0.0002143866,0.0004404862,0.02757055,0.0003396346,0.0002034733,0.003909013,0.004420883,0.01408005,0.05387925,0.3312492,0.5634227,0.0002702406],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3621681,0.005581183,0.3699542,0.006030999,0.00111888,0.0006718934,0.007937334,0.005792965,0.2407444],"genre_scores_gemma":[0.6968777,0.001906448,0.2480111,0.0007015489,0.0004850154,0.0002070723,0.005079387,0.0003974274,0.04633437],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01139697,"threshold_uncertainty_score":0.03812671,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01962410501615979,"score_gpt":0.2533599407734151,"score_spread":0.2337358357572553,"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."}}