{"id":"W1984599252","doi":"10.1186/1471-2105-12-299","title":"Ranking insertion, deletion and nonsense mutations based on their effect on genetic information","year":2011,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Biology; Genetics; Nonsense mutation; Indel; INDEL Mutation; Coding region; Mutation; Context (archaeology); Computational biology; Single-nucleotide polymorphism; Gene; Missense mutation; Genotype","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":[0.001975683,0.0006916038,0.0009016835,0.002960638,0.0004357209,0.001016401,0.0007097718,0.0007036019,0.001635207],"category_scores_gemma":[0.006548491,0.0001577378,0.0007006837,0.00164944,0.0005034846,0.0005219121,0.0003633629,0.0005696432,0.0003540242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000674916,"about_ca_system_score_gemma":0.001202333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001932995,"about_ca_topic_score_gemma":0.005921981,"domain_scores_codex":[0.9991271,0.0002655493,0.00008641116,0.0001473643,0.0003042303,0.00006929659],"domain_scores_gemma":[0.9935189,0.004854913,0.0006930176,0.0001765333,0.0004815501,0.0002750596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002726009,0.000891009,0.3008624,0.001786726,0.001152624,0.0007172933,0.0002412993,0.3295607,0.07045374,0.007601961,0.005635221,0.278371],"study_design_scores_gemma":[0.0002063614,0.000941916,0.08444728,0.0001102896,0.0004397257,0.0008217124,0.000135473,0.8686023,0.0251207,0.01558145,0.003498493,0.00009426438],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8584221,0.001737527,0.1333051,0.0007278509,0.00007314153,0.0001932826,0.002666525,0.001085538,0.001788988],"genre_scores_gemma":[0.8901097,0.000614938,0.1051668,0.0001790804,0.00005042113,0.00009464563,0.003195214,0.0000901621,0.0004990738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002960638,"threshold_uncertainty_score":0.01044858,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01021817641883853,"score_gpt":0.2079564167870597,"score_spread":0.1977382403682212,"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."}}