{"id":"W2051395158","doi":"10.1007/s10482-011-9598-6","title":"Metaxa: a software tool for automated detection and discrimination among ribosomal small subunit (12S/16S/18S) sequences of archaea, bacteria, eukaryotes, mitochondria, and chloroplasts in metagenomes and environmental sequencing datasets","year":2011,"lang":"en","type":"article","venue":"Antonie van Leeuwenhoek","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Tartu Ülikool; Göteborgs Universitet","keywords":"Biology; Genome; Ribosomal RNA; Metagenomics; Archaea; Computational biology; Gene; Eukaryote; Nuclear gene; Genetics; Chloroplast; Evolutionary biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.007866045,0.00427319,0.003207272,0.006769382,0.002184986,0.002822758,0.003639366,0.001780541,0.01283433],"category_scores_gemma":[0.008772688,0.00406785,0.003823466,0.005061807,0.0009161958,0.003129016,0.002816236,0.003904306,0.006056902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008826181,"about_ca_system_score_gemma":0.002079987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002814588,"about_ca_topic_score_gemma":0.004060903,"domain_scores_codex":[0.9970921,0.0005721608,0.0005925972,0.0009473773,0.0006143037,0.0001813898],"domain_scores_gemma":[0.995779,0.002383209,0.0005980482,0.0006834968,0.0004021141,0.0001541493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.006808832,0.0008861711,0.03512274,0.01323132,0.006650637,0.001447196,0.003638254,0.009284094,0.2033419,0.01527849,0.293105,0.4112054],"study_design_scores_gemma":[0.003467127,0.001026667,0.07705925,0.001945793,0.003469753,0.002632635,0.001325976,0.1213338,0.2427078,0.04007297,0.5037934,0.001164717],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01765876,0.001313019,0.485402,0.0002910511,0.0002906856,0.0008773911,0.1016894,0.3896108,0.00286695],"genre_scores_gemma":[0.041416,0.0008994538,0.8008836,0.0004040977,0.0001201388,0.003414148,0.1202822,0.02983118,0.002749069],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.01283433,"threshold_uncertainty_score":0.04293513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0180226755058124,"score_gpt":0.2131836961156122,"score_spread":0.1951610206097998,"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."}}