{"id":"W4297394770","doi":"10.1101/2022.09.26.509576","title":"Multi-factorial examination of amplicon sequencing workflows from sample preparation to bioinformatic analysis","year":2022,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"U.S. National Library of Medicine; National Institutes of Health; Michael Smith Health Research BC; University of Pittsburgh","keywords":"Microbiome; Amplicon; Computational biology; Metagenomics; Amplicon sequencing; Workflow; Microbial ecology; Biology; Fidelity; Computer science; Bioinformatics; Polymerase chain reaction; Genetics; Gene; 16S ribosomal RNA; Bacteria","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":[0.01709712,0.001310553,0.001125362,0.001248611,0.0006571471,0.00256777,0.0007968958,0.000733654,0.001011505],"category_scores_gemma":[0.02693293,0.0006896129,0.001452905,0.001216335,0.0008014395,0.001220331,0.001570744,0.0009776149,0.0005648106],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007292166,"about_ca_system_score_gemma":0.001414093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00164166,"about_ca_topic_score_gemma":0.00142858,"domain_scores_codex":[0.9867997,0.005640776,0.002155524,0.002442121,0.002165401,0.0007965305],"domain_scores_gemma":[0.9716642,0.01619861,0.003381621,0.003119481,0.004810386,0.0008257836],"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":[0.007632694,0.002130496,0.02152428,0.001258905,0.0006030158,0.000108437,0.0006023979,0.006965153,0.898225,0.0003438494,0.0006561725,0.0599496],"study_design_scores_gemma":[0.0002251531,0.01595084,0.08732085,0.0001464962,0.00106295,0.0002532,0.0005698773,0.02651548,0.8592136,0.0007243853,0.007735691,0.0002815361],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9361446,0.001351209,0.05646313,0.0002677285,0.0002016862,0.002087813,0.00139821,0.001094742,0.0009909703],"genre_scores_gemma":[0.8217503,0.001417801,0.164057,0.0004292302,0.0001232571,0.005841336,0.003223779,0.001037429,0.00211989],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01709712,"threshold_uncertainty_score":0.09041935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02058964686681869,"score_gpt":0.2616671851603014,"score_spread":0.2410775382934827,"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."}}