{"id":"W2950635543","doi":"10.1101/672295","title":"PICRUSt2: An improved and customizable approach for metagenome inference","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":736,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"National Institute on Alcohol Abuse and Alcoholism; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; GlaxoSmithKline","keywords":"Metagenomics; Inference; Gene prediction; DNA sequencing; Reference database; Genomics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005503371,0.0005072,0.0005564913,0.0001186132,0.0001533545,0.0001723347,0.0004800227,0.0008266408,0.000009889165],"category_scores_gemma":[0.0001018174,0.0005304111,0.0001312788,0.0001030312,0.0001003975,0.00001316604,0.0005403575,0.0003929858,0.000006859865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006021722,"about_ca_system_score_gemma":0.0007909454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005390699,"about_ca_topic_score_gemma":0.000003189326,"domain_scores_codex":[0.9974992,0.00009351916,0.0003934239,0.001313275,0.0001010278,0.0005995491],"domain_scores_gemma":[0.9977215,0.0000166162,0.0002999162,0.001325496,0.0003459079,0.0002905935],"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":[0.00007952563,0.0001175972,0.001359351,0.000665466,0.0001207584,7.408315e-7,0.000005470529,0.0001139771,0.9971759,0.0001487653,0.0002096509,0.000002776207],"study_design_scores_gemma":[0.003595489,0.00107892,0.03983725,0.0001650734,0.0004583699,9.742103e-8,0.00001743853,0.008515635,0.8824972,0.000005464917,0.06092642,0.002902641],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9551891,0.003098335,0.03807903,0.00005602855,0.0005712342,0.002162431,0.0007211122,0.00009522937,0.00002746471],"genre_scores_gemma":[0.9661506,0.0005823057,0.03188225,0.0003364612,0.0004573468,0.0004129909,0.00001247547,0.000126668,0.00003886603],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1146787,"threshold_uncertainty_score":0.9997147,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01629389083823218,"score_gpt":0.2457617375584072,"score_spread":0.229467846720175,"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."}}