{"id":"W2963276645","doi":"10.1038/s41587-019-0209-9","title":"Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2","year":2019,"lang":"en","type":"letter","venue":"Nature Biotechnology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24006,"is_retracted":false,"has_abstract":false,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia; Dalhousie University","funders":"National Institute of Environmental Health Sciences; National Institute of General Medical Sciences; Medical Research Council; Universitetet i Bergen; Agricultural Research Service; Washington Research Foundation; Haukeland Universitetssjukehus; Medizinische Universität Graz; San Diego State University; National Institutes of Health; National Institute on Minority Health and Health Disparities; Karl-Franzens-Universität Graz; National Cancer Institute; Tianjin University; Max-Planck-Gesellschaft; Chinese Academy of Sciences; Karolinska Institutet; Stockholms Universitet; National Science Foundation; Universidad del Atlántico; Florida Atlantic University; Arizona Board of Regents; Natural Sciences and Engineering Research Council of Canada; U.S. Department of Agriculture; Alfred P. Sloan Foundation; Massachusetts Institute of Technology; National Health and Medical Research Council; Northern Arizona University","keywords":"Microbiome; Scalability; Extensibility; Computer science; Computational biology; Data science; Biology; Bioinformatics; Database; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01143366,0.0006483021,0.001076964,0.0009381196,0.0008657405,0.003858916,0.003027731,0.005031667,0.007161015],"category_scores_gemma":[0.04209846,0.001315823,0.0009287162,0.0008436229,0.001901004,0.003639096,0.004310675,0.01087986,0.006929642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001157765,"about_ca_system_score_gemma":0.001914825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001338809,"about_ca_topic_score_gemma":0.004252228,"domain_scores_codex":[0.9915012,0.002535364,0.0006551084,0.0008274668,0.003753969,0.0007268661],"domain_scores_gemma":[0.969955,0.01694009,0.001327877,0.005293158,0.004617264,0.001866696],"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":[0.001301839,0.000154407,0.002824401,0.0008413395,0.000214994,0.000985114,0.000566214,0.003039372,0.04500173,0.02357719,0.7338379,0.1876557],"study_design_scores_gemma":[0.0005059716,0.0002560813,0.001703225,0.0003124452,0.00008557158,0.001040044,0.0001963841,0.03951914,0.03612956,0.09353937,0.826415,0.0002972236],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.0118293,0.006596631,0.4672543,0.4254668,0.05367685,0.0005563499,0.006857492,0.01753109,0.01023123],"genre_scores_gemma":[0.1094191,0.006589737,0.5819476,0.2225978,0.0334462,0.002865232,0.01047063,0.004908675,0.02775504],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01143366,"threshold_uncertainty_score":0.06046772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02046194341237909,"score_gpt":0.3134125506173104,"score_spread":0.2929506072049314,"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."}}