{"id":"W4309908917","doi":"10.1093/nar/gkac1083","title":"DNA Data Bank of Japan (DDBJ) update report 2022","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Bioscience Database Center; Core Research for Evolutional Science and Technology; Japan Science and Technology Agency; Ministry of Education, Culture, Sports, Science and Technology; Research Organization of Information and Systems; Institute of Genetics; Japan Agency for Medical Research and Development","keywords":"Data bank; Biology; Genomics; Database; DNA sequencing; Library science; Bioinformatics; Genetics; Computational biology; Genome; DNA; Gene; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007227127,0.001799181,0.002711439,0.0121834,0.001201604,0.004645831,0.002974442,0.001649942,0.04933909],"category_scores_gemma":[0.01819286,0.001491551,0.0009148856,0.0214714,0.0004887939,0.002923938,0.00204668,0.003493815,0.0801449],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00186505,"about_ca_system_score_gemma":0.01043069,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0242367,"about_ca_topic_score_gemma":0.02579804,"domain_scores_codex":[0.9966556,0.0006417568,0.0008623199,0.0004315582,0.001131095,0.0002777031],"domain_scores_gemma":[0.9835709,0.001983281,0.001919309,0.002130578,0.008882326,0.001513595],"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":[0.0002153234,0.00005594736,0.001278196,0.001375916,0.00005283478,0.00006740679,0.00008270888,0.0001310324,0.0009337926,0.001040376,0.9485743,0.04619214],"study_design_scores_gemma":[0.00004575836,0.00001522976,0.002378037,0.000266062,0.00005788803,0.00006236516,0.00004883753,0.00008895286,0.0004368309,0.0005518275,0.9960188,0.00002938427],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.001169773,0.00410144,0.00550055,0.002591634,0.00228429,0.0003627129,0.9650822,0.00428495,0.01462255],"genre_scores_gemma":[0.0008803689,0.003321432,0.01175197,0.0007648701,0.0002998847,0.0005186774,0.9737133,0.0007732576,0.007976227],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04933909,"threshold_uncertainty_score":0.1650557,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06080130570690578,"score_gpt":0.3460074153676005,"score_spread":0.2852061096606948,"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."}}