{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002289044,0.001847964,0.001168595,0.00635648,0.001898074,0.001170831,0.001154789,0.001495941,0.001967808],"category_scores_gemma":[0.002806105,0.0009139068,0.001266928,0.003032244,0.0009262842,0.000747042,0.002030079,0.001294313,0.002019836],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00114017,"about_ca_system_score_gemma":0.003641436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008930026,"about_ca_topic_score_gemma":0.03535052,"domain_scores_codex":[0.9953845,0.0005011939,0.0003364414,0.00138685,0.002078654,0.0003124212],"domain_scores_gemma":[0.9979559,0.0003067685,0.0002907449,0.0003699237,0.0008968916,0.0001797954],"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":[0.00007313155,0.00009772691,0.006963121,0.0002629646,0.0001034794,0.00008967848,0.0002472527,0.0002658079,0.9631812,0.0002924065,0.0005137114,0.02790951],"study_design_scores_gemma":[0.00004383976,0.0004570121,0.09577795,0.0002841831,0.0004210466,0.001471622,0.0004049604,0.008692202,0.8563084,0.0009369912,0.03499525,0.0002065854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.190406,0.003568786,0.7726507,0.0004396608,0.0002080173,0.00268069,0.01769766,0.005459796,0.006888697],"genre_scores_gemma":[0.1149023,0.001746505,0.863183,0.0004856223,0.00003907764,0.003113686,0.01086473,0.0003987421,0.005266406],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008930026,"threshold_uncertainty_score":0.0177561,"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."}}