{"id":"W1499378530","doi":"10.1111/j.1574-6968.2011.02274.x","title":"V-REVCOMP: automated high-throughput detection of reverse complementary 16S rRNA gene sequences in large environmental and taxonomic datasets","year":2011,"lang":"en","type":"article","venue":"FEMS Microbiology Letters","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Engineering and Physical Sciences Research Council; Genome British Columbia; Tula Foundation","keywords":"Biology; 16S ribosomal RNA; Software; DNA sequencing; Computational biology; Sequence (biology); Sequence analysis; Gene; Genetics; Computer science","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":[0.005468909,0.003042256,0.001849469,0.003716429,0.0008908639,0.002249259,0.003012148,0.001734399,0.004267539],"category_scores_gemma":[0.01027482,0.001737082,0.002404161,0.002164822,0.000755347,0.002186011,0.002351854,0.00194876,0.005919708],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004670906,"about_ca_system_score_gemma":0.001409282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001338624,"about_ca_topic_score_gemma":0.002322803,"domain_scores_codex":[0.9965243,0.0006547504,0.000364469,0.00119063,0.001040579,0.0002253107],"domain_scores_gemma":[0.9936382,0.00341476,0.0009912434,0.0009333249,0.0007972225,0.0002253581],"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":[0.002964972,0.0006307224,0.03589205,0.006899398,0.002100654,0.001648315,0.001601126,0.01243776,0.4293759,0.003916187,0.1348703,0.3676627],"study_design_scores_gemma":[0.0005850523,0.0009660349,0.0348722,0.0008271141,0.0005315592,0.003138699,0.0005813701,0.2516366,0.5558056,0.006287032,0.1439545,0.000814162],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.08356462,0.001725476,0.4803189,0.0002985061,0.0003785678,0.0007606755,0.04160483,0.3874655,0.003882897],"genre_scores_gemma":[0.1111769,0.0006267686,0.782028,0.0004480186,0.0001160493,0.00131711,0.08068013,0.02151258,0.002094573],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005468909,"threshold_uncertainty_score":0.02892268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01167431072931845,"score_gpt":0.201763213783751,"score_spread":0.1900889030544325,"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."}}