{"id":"W4239734004","doi":"10.1093/nar/gkaa967","title":"The international nucleotide sequence database collaboration","year":2020,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":254,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Directorate for Biological Sciences; National Institutes of Health; Institute of Genetics; U.S. National Library of Medicine; Ministry of Education, Culture, Sports, Science and Technology; Wellcome Trust; European Commission; National Bioscience Database Center; Japan Agency for Medical Research and Development; European Molecular Biology Laboratory; European Bioinformatics Institute; Gordon and Betty Moore Foundation","keywords":"GenBank; Biology; Metadata; Library science; Nucleic acid sequence; Sequence database; Database; Genetics; World Wide Web; 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":[0.02910337,0.001967266,0.004035246,0.01922544,0.00343404,0.01094426,0.004997234,0.003304346,0.08149829],"category_scores_gemma":[0.03685067,0.0009530994,0.001038151,0.04048763,0.00150534,0.004323746,0.006464555,0.00526089,0.09415197],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002926767,"about_ca_system_score_gemma":0.02372011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007888505,"about_ca_topic_score_gemma":0.005740253,"domain_scores_codex":[0.9752048,0.006252491,0.006321556,0.004782064,0.005831004,0.001608111],"domain_scores_gemma":[0.9496983,0.006640861,0.004693409,0.01223884,0.01819246,0.008536298],"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":[0.0007492522,0.0001165436,0.002833305,0.002324918,0.0001221178,0.0002744826,0.0005769874,0.0002429213,0.002632424,0.02266433,0.8213454,0.1461174],"study_design_scores_gemma":[0.00005951825,0.00002122049,0.001154664,0.0007341919,0.00003967093,0.0001108993,0.0001296347,0.0001516847,0.000444763,0.004733288,0.9924002,0.00002027849],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.003887497,0.02245737,0.04681989,0.02189612,0.01113805,0.001392574,0.5826752,0.01461519,0.2951181],"genre_scores_gemma":[0.01342177,0.0108707,0.1253382,0.006285596,0.001329748,0.003116425,0.7909932,0.004545827,0.04409841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.08149829,"threshold_uncertainty_score":0.272639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07018148120026386,"score_gpt":0.3550611345353628,"score_spread":0.2848796533350989,"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."}}