{"id":"W2227395312","doi":"10.1186/s13059-016-1037-6","title":"An expanded evaluation of protein function prediction methods shows an improvement in accuracy","year":2016,"lang":"en","type":"article","venue":"Genome biology","topic":"Bioinformatics and Genomic Networks","field":"Biochemistry, Genetics and Molecular Biology","cited_by":452,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Lawrence Berkeley National Laboratory; National Center for Advancing Translational Sciences; National Institute of General Medical Sciences; KU Leuven; National Institute of Mental Health; Natural Sciences and Engineering Research Council of Canada; Instituto de Salud Carlos III; Biotechnology and Biological Sciences Research Council; Office of Science; Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja; China Scholarship Council; Parkinson's UK; National Key Research and Development Program of China; U.S. National Library of Medicine; British Heart Foundation; Alexander von Humboldt-Stiftung; Fundação de Amparo à Pesquisa do Estado de São Paulo; Università degli Studi di Padova; U.S. Department of Energy; National Natural Science Foundation of China; Microsoft Research; Directorate for Biological Sciences; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; FP7 Research Potential of Convergence Regions; Gordon and Betty Moore Foundation; National Science Foundation","keywords":"Gene ontology; Bottleneck; Function (biology); Context (archaeology); Annotation; Computer science; Set (abstract data type); Computational biology; Protein function prediction; Ontology; Field (mathematics); Biology; Machine learning; Data mining; Artificial intelligence; Protein function; Gene; Genetics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002014279,0.0001195135,0.0001420941,0.00007266535,0.00003014674,0.000005788911,0.0001352916,0.0002413194,0.00005991933],"category_scores_gemma":[0.00006888002,0.00008712275,0.00003938986,0.00005596521,0.00005539727,0.0000178619,0.00005021688,0.00004774376,0.000002374459],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004828624,"about_ca_system_score_gemma":0.00008418648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001770607,"about_ca_topic_score_gemma":0.0000462056,"domain_scores_codex":[0.9987311,0.0003299316,0.00037128,0.0002546238,0.0000789148,0.0002341505],"domain_scores_gemma":[0.9992373,0.00001073705,0.0001803709,0.0003783125,0.0001264391,0.00006687058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001038533,0.00005965589,0.001021478,0.000004966986,0.00001868235,1.482743e-8,0.00005066384,0.00003906864,0.7415694,0.0002005466,0.000004634824,0.256927],"study_design_scores_gemma":[0.007044812,0.01228772,0.06432647,0.00003713144,0.0001419364,0.00001053323,0.0006034106,0.008118289,0.8653637,0.02836117,0.01288041,0.0008244678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8685451,0.000343646,0.1300977,0.00002350321,0.000205566,0.0005660483,0.00004287604,0.000008068373,0.0001675201],"genre_scores_gemma":[0.9956825,0.0000407867,0.003437552,0.00006211522,0.0002676374,0.000146994,0.0003123764,0.00001082635,0.00003915475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2561025,"threshold_uncertainty_score":0.3552763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02814504185848216,"score_gpt":0.3355122508901335,"score_spread":0.3073672090316513,"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."}}