{"id":"W4390273482","doi":"10.1111/1462-2920.16566","title":"Mock microbial community meta‐analysis using different trimming of amplicon read lengths","year":2023,"lang":"en","type":"article","venue":"Environmental Microbiology","topic":"Gut microbiota and health","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Alliance de recherche numérique du Canada; Ocean Frontier Institute; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Trimming; Amplicon; Biology; Metagenomics; Trim; Amplicon sequencing; False positive paradox; Computational biology; Relative species abundance; Heuristics; Evolutionary biology; Abundance (ecology); Computer science; 16S ribosomal RNA; Genetics; Artificial intelligence; Ecology; Polymerase chain reaction; Gene","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":[0.002600672,0.001352317,0.001147364,0.001214127,0.0009843239,0.001352862,0.000942347,0.001059253,0.001310601],"category_scores_gemma":[0.004011211,0.0004813349,0.002090218,0.001086318,0.0004167765,0.000820437,0.0008846354,0.001044256,0.0009008315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004977256,"about_ca_system_score_gemma":0.000648959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001352186,"about_ca_topic_score_gemma":0.002143126,"domain_scores_codex":[0.9982583,0.0004653919,0.0001411671,0.0005808127,0.000415293,0.0001390578],"domain_scores_gemma":[0.9984838,0.000484782,0.0001681266,0.000363299,0.0004045718,0.00009542819],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"meta_analysis","study_design_scores_codex":[0.002651537,0.0005791248,0.05514839,0.001223645,0.001923035,0.0002472875,0.0008106621,0.0180091,0.8501759,0.001022039,0.000868168,0.06734118],"study_design_scores_gemma":[0.0001132158,0.002422472,0.100782,0.0001218653,0.001494365,0.0004038826,0.0005168147,0.1769649,0.7034196,0.003782776,0.009682548,0.0002956475],"study_design_candidate":"meta_analysis","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.825705,0.001421827,0.1630982,0.0001354285,0.000159921,0.0004509002,0.004277422,0.003083157,0.001668144],"genre_scores_gemma":[0.7787293,0.0003724808,0.2098126,0.0002293832,0.00003317122,0.0007290963,0.008552564,0.000518576,0.001022919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002600672,"threshold_uncertainty_score":0.01375383,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04889093585536401,"score_gpt":0.2862928708502343,"score_spread":0.2374019349948703,"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."}}