{"id":"W4284889270","doi":"10.1093/molbev/msac153","title":"Pseudofinder: Detection of Pseudogenes in Prokaryotic Genomes","year":2022,"lang":"en","type":"article","venue":"Molecular Biology and Evolution","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Japan Society for the Promotion of Science; Natural Sciences and Engineering Research Council of Canada; Gordon and Betty Moore Foundation; National Aeronautics and Space Administration; National Science Foundation","keywords":"Pseudogene; Biology; Genome; Gene; Genetics; Identification (biology); Bacterial genome size; Computational biology; Negative selection; Phylogenetic tree; Evolutionary biology; Ecology","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":[0.002968694,0.001853032,0.001181124,0.004603153,0.001035021,0.001921638,0.001778231,0.001746941,0.004281468],"category_scores_gemma":[0.01191218,0.0008386021,0.001362441,0.002391875,0.0006346726,0.002499084,0.00214892,0.001244228,0.003350607],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004549729,"about_ca_system_score_gemma":0.0009719317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005805325,"about_ca_topic_score_gemma":0.0007697769,"domain_scores_codex":[0.9980789,0.0002979409,0.0002018493,0.0006220384,0.000659714,0.0001395062],"domain_scores_gemma":[0.9966301,0.001527528,0.0007312297,0.0004441155,0.0004471802,0.0002197879],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004673903,0.0003342977,0.05743096,0.005553394,0.0007312159,0.002083714,0.002026054,0.006429857,0.5137057,0.0070714,0.06695493,0.3330046],"study_design_scores_gemma":[0.0003329265,0.0007559605,0.05436635,0.000604204,0.0003720019,0.00619429,0.000671627,0.163678,0.5985667,0.01526178,0.1585658,0.00063041],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1878653,0.003319937,0.5608391,0.0005329431,0.0004876603,0.0003753591,0.03857655,0.2038378,0.004165483],"genre_scores_gemma":[0.2119893,0.0009738457,0.7089702,0.0004230582,0.00008649301,0.0005620645,0.06323492,0.01060252,0.003157628],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004603153,"threshold_uncertainty_score":0.01570016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005678173363596059,"score_gpt":0.224681510451683,"score_spread":0.219003337088087,"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."}}