{"id":"W2127143129","doi":"10.1093/bioinformatics/btl116","title":"PseudoPipe: an automated pseudogene identification pipeline","year":2006,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":212,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; University of Toronto","funders":"National Institutes of Health; National Human Genome Research Institute; University of Toronto","keywords":"Pseudogene; Genome; Biology; Genetics; Homology (biology); Computational biology; Gene; Retrotransposon; Intergenic region; Transposable element","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":[0.001136629,0.001185026,0.0007770127,0.001853638,0.0009918333,0.001325961,0.002356638,0.0008506719,0.01129434],"category_scores_gemma":[0.003233224,0.0008791793,0.001079573,0.0013081,0.0004221937,0.002251429,0.00130251,0.0008277869,0.004578443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005525624,"about_ca_system_score_gemma":0.001593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002368658,"about_ca_topic_score_gemma":0.002617069,"domain_scores_codex":[0.999464,0.00009401933,0.00004678714,0.0001699904,0.0001814485,0.00004377174],"domain_scores_gemma":[0.999027,0.0003946695,0.0000880927,0.0001316213,0.0002806041,0.00007794034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002539277,0.0004203075,0.007461293,0.001858829,0.0002792868,0.001174115,0.0004148044,0.03741285,0.07250059,0.01574076,0.2194682,0.6407297],"study_design_scores_gemma":[0.0005122904,0.0002692954,0.003793917,0.00007351975,0.00007615396,0.001413429,0.0001325259,0.7993017,0.07063017,0.03316265,0.09044697,0.0001874348],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02157127,0.0004309186,0.7822849,0.0003679293,0.0001281821,0.0003961083,0.01407844,0.1779924,0.002749913],"genre_scores_gemma":[0.08331233,0.0003316634,0.855374,0.0002741805,0.00005328025,0.0005572363,0.05074949,0.00516409,0.004183701],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01129434,"threshold_uncertainty_score":0.03778332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039699376225014,"score_gpt":0.2506661242629637,"score_spread":0.2402691305007136,"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."}}