{"id":"W2335786001","doi":"10.1038/ismej.2015.249","title":"High-resolution phylogenetic microbial community profiling","year":2016,"lang":"en","type":"article","venue":"The ISME Journal","topic":"Microbial Community Ecology and Physiology","field":"Environmental Science","cited_by":322,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Office of Science; University of British Columbia; Joint Genome Institute; Tula Foundation; Canadian Institute for Advanced Research; U.S. Department of Energy","keywords":"Biology; Phylogenetic tree; Microbial population biology; Metagenomics; Community structure; 16S ribosomal RNA; Amplicon; Phylogenetics; In silico; Computational biology; Ribosomal RNA; Sanger sequencing; Evolutionary biology; Genetics; Ecology; DNA sequencing; Gene; Bacteria; Polymerase chain reaction","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":[0.0006721267,0.0005128559,0.00048933,0.001641186,0.0004601238,0.0006326368,0.0003443066,0.0005571159,0.00136588],"category_scores_gemma":[0.001371051,0.000252703,0.000479792,0.001515944,0.0002322896,0.0007761387,0.0009052175,0.0005811963,0.000968261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002019849,"about_ca_system_score_gemma":0.0002545544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006861822,"about_ca_topic_score_gemma":0.001135698,"domain_scores_codex":[0.9991663,0.0002239013,0.00004784756,0.0002651437,0.0002048752,0.00009197712],"domain_scores_gemma":[0.9994904,0.0001153748,0.00007685115,0.00008328846,0.0001801208,0.00005397196],"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":[0.000142497,0.00004769001,0.01142312,0.0001740038,0.00004153841,0.00007141008,0.0002432206,0.002448559,0.9561351,0.0007232826,0.0002302792,0.02831944],"study_design_scores_gemma":[0.00005290921,0.0008650637,0.1904249,0.0001186189,0.0002246591,0.001164032,0.0008915268,0.1769616,0.5949901,0.008203196,0.02597685,0.0001263743],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6857287,0.001491027,0.2982846,0.0002337923,0.00004150706,0.0002177708,0.008511289,0.001198017,0.004293317],"genre_scores_gemma":[0.7435074,0.000794932,0.2468496,0.0001350309,0.00002477829,0.0002478984,0.006654481,0.0001680552,0.001617823],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001641186,"threshold_uncertainty_score":0.004569292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01708107529918448,"score_gpt":0.2247850812880467,"score_spread":0.2077040059888622,"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."}}