{"id":"W2345132669","doi":"10.1186/s40168-016-0166-1","title":"A comprehensive method for amplicon-based and metagenomic characterization of viruses, bacteria, and eukaryotes in freshwater samples","year":2016,"lang":"en","type":"article","venue":"Microbiome","topic":"Bacteriophages and microbial interactions","field":"Environmental Science","cited_by":106,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Saskatchewan; Canadian Institute for Advanced Research; University of British Columbia; BC Centre for Disease Control","funders":"Natural Sciences and Engineering Research Council of Canada; SFU Community Trust Endowment Fund; Simon Fraser University; Genome British Columbia; Michael Smith Health Research BC; Public Health Agency; Public Health Agency of Canada; Canadian Institutes of Health Research; Mitacs; Genome Canada","keywords":"Metagenomics; Biology; Amplicon; Microbiome; 16S ribosomal RNA; Ribosomal RNA; Computational biology; Microbial ecology; Bacteria; Amplicon sequencing; Bacterial taxonomy; Deep sequencing; Phylum; Gene; Genome; Polymerase chain reaction; Genetics","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":[],"consensus_categories":[],"category_scores_codex":[0.00008408468,0.0001185479,0.0001964138,0.00007424376,0.0000407974,0.00002537451,0.00006593746,0.00005195138,0.0005083433],"category_scores_gemma":[0.000007381387,0.00008776543,0.00003418306,0.00006593442,0.0001115652,0.0001695983,0.00007839091,0.00002631476,0.00001367423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004525802,"about_ca_system_score_gemma":0.000005315873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006115561,"about_ca_topic_score_gemma":0.0004124375,"domain_scores_codex":[0.9993029,0.00004604267,0.0002160289,0.0002540622,0.00002164009,0.0001593018],"domain_scores_gemma":[0.9996362,0.0001084556,0.00009296742,0.0001150584,0.00001007155,0.00003719047],"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":[0.00005308097,0.00003092631,0.002058573,0.00002627831,0.00001103827,3.755912e-7,0.000108128,6.068948e-7,0.990995,0.000005368813,0.00004043831,0.006670127],"study_design_scores_gemma":[0.0006669217,0.00005043692,0.2269538,0.00003728248,0.00001438515,0.000007976601,0.00001035602,0.00003240297,0.7293463,0.00002692547,0.04273422,0.0001189984],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987675,0.00002227949,0.0106851,0.000291596,0.0000582208,0.0002904796,0.0009629991,0.000009884509,0.000004410217],"genre_scores_gemma":[0.9670578,0.00003488908,0.03217077,0.0004390353,0.00001631319,0.0000305145,0.00008113404,0.00002115344,0.0001484015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2616488,"threshold_uncertainty_score":0.5566003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02110176569183673,"score_gpt":0.2609354436712967,"score_spread":0.23983367797946,"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."}}