{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001754298,0.00009206861,0.0001194509,0.00008389891,0.0001058028,0.000001911698,0.0000769194,0.00007228724,0.000003875303],"category_scores_gemma":[0.00001684986,0.00009808016,0.00004313505,0.0001015923,0.00008982752,4.699339e-7,0.0001802174,0.00006453905,4.19322e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000198234,"about_ca_system_score_gemma":0.00003058044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004804818,"about_ca_topic_score_gemma":0.00004187926,"domain_scores_codex":[0.9992738,0.0001221146,0.0001601899,0.000248561,0.0000425635,0.000152727],"domain_scores_gemma":[0.9997515,0.00000536208,0.00006257465,0.0001357167,0.00002429821,0.0000205398],"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":[0.00006333855,0.00003406271,0.08808915,0.000008369634,0.00002990351,0.000001154952,0.00003660929,0.0004541129,0.9088786,0.0006680316,0.000004660605,0.001732045],"study_design_scores_gemma":[0.001433582,0.001890316,0.4400648,0.000005321023,0.00004768684,0.0001133151,0.0004720608,0.0005537601,0.5417734,0.009763095,0.003454905,0.0004277684],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9841849,0.01259125,0.002776304,0.00005867734,0.0001164711,0.0001523399,0.00001507302,0.000002118043,0.0001028532],"genre_scores_gemma":[0.9993671,0.0002363449,0.0002018821,0.00005149799,0.00002495485,0.00005895419,0.00002451268,0.00000834607,0.00002646738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3671052,"threshold_uncertainty_score":0.3999593,"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."}}