{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001703538,0.0002112338,0.0002523853,0.0000894918,0.0001070733,0.00002225327,0.000082643,0.0001000349,0.000005058721],"category_scores_gemma":[0.00005297863,0.0002022189,0.00003688952,0.00004295773,0.000249465,0.00001294391,0.0001585059,0.00005509379,2.551625e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001745453,"about_ca_system_score_gemma":0.00002485153,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003923349,"about_ca_topic_score_gemma":0.001548833,"domain_scores_codex":[0.9989462,0.00005865609,0.0002805479,0.0004253614,0.00006474157,0.0002244726],"domain_scores_gemma":[0.9995536,0.00004039859,0.0001573743,0.0001666904,0.00002040395,0.00006159051],"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":[0.00009164315,0.00003254488,0.04463725,0.00009247453,0.0001039826,0.000004189199,0.0009863187,0.000006226433,0.9472954,0.000006929441,0.000002446719,0.006740595],"study_design_scores_gemma":[0.000864939,0.0005854411,0.4249237,0.00003174876,0.0001248686,0.00003746315,0.0007366384,0.000521257,0.5715585,0.0001721002,0.0001380673,0.0003052869],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952221,0.003046014,0.0006278487,0.000007383918,0.00006123295,0.0004000554,0.0006204442,0.000007958604,0.000006959667],"genre_scores_gemma":[0.9908522,0.00104677,0.007620397,0.00001595258,0.00002745185,0.0000565325,0.0003423986,0.00002048078,0.00001783049],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3802865,"threshold_uncertainty_score":0.8246248,"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."}}