{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003407876,0.003304634,0.00196652,0.003521569,0.001272833,0.003705485,0.004478101,0.001739472,0.01225286],"category_scores_gemma":[0.01218778,0.002187877,0.004020925,0.002580022,0.0006975121,0.002813652,0.003620548,0.003831392,0.007508068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000851872,"about_ca_system_score_gemma":0.002580568,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006357341,"about_ca_topic_score_gemma":0.01054266,"domain_scores_codex":[0.9985758,0.0002786752,0.0001280547,0.0004882996,0.0004198815,0.0001092218],"domain_scores_gemma":[0.9975989,0.001050815,0.0001417553,0.0007046291,0.0003429669,0.0001608501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001947784,0.0004942776,0.03226538,0.00309264,0.004228542,0.001619824,0.00182185,0.1286496,0.0653512,0.03132647,0.2599016,0.4693007],"study_design_scores_gemma":[0.0003353939,0.0001065021,0.00400552,0.0001406009,0.0003057245,0.0007458186,0.0001285273,0.8215723,0.0305439,0.03028415,0.1115604,0.0002711089],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00784033,0.0002411004,0.8042046,0.0001916915,0.0003219534,0.0001752052,0.01019493,0.1743516,0.002478438],"genre_scores_gemma":[0.05169602,0.0002371945,0.8821687,0.0003547586,0.0001635737,0.0005967284,0.02859696,0.0337244,0.002461619],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01225286,"threshold_uncertainty_score":0.04098994,"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."}}