{"id":"W4308616119","doi":"10.1093/nar/gkac966","title":"FAVOR: functional annotation of variants online resource and annotator for variation across the human genome","year":2022,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":143,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"National Institute of Environmental Health Sciences; National Human Genome Research Institute; National Cancer Institute; National Heart, Lung, and Blood Institute; National Institutes of Health","keywords":"Annotation; Biology; Computational biology; Genome; Human genome; Genetics; Gene","routes":{"ca_aff":true,"ca_fund":false,"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":[0.002783129,0.002354788,0.001481341,0.005027867,0.001535843,0.001925698,0.00352537,0.001504793,0.0723521],"category_scores_gemma":[0.00607449,0.001206584,0.001402416,0.004366269,0.0004564703,0.001821095,0.004481861,0.001688574,0.03703812],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007807189,"about_ca_system_score_gemma":0.002073386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00376521,"about_ca_topic_score_gemma":0.007130271,"domain_scores_codex":[0.9986781,0.0002383507,0.0001882563,0.0003836897,0.0003728505,0.0001387069],"domain_scores_gemma":[0.9970858,0.001265991,0.0003647629,0.0005794377,0.0004269276,0.0002771334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001243942,0.000110192,0.006867553,0.003379239,0.000231742,0.0009258324,0.0005964343,0.001299335,0.01866501,0.005374525,0.9018638,0.05944243],"study_design_scores_gemma":[0.0006434372,0.0001385085,0.0147962,0.0007013744,0.0002980487,0.002248744,0.0003034566,0.01052757,0.01950789,0.01536974,0.9351853,0.0002797565],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.005918295,0.001013616,0.07470142,0.0005894491,0.0004038333,0.0003452137,0.8230924,0.0827445,0.01119128],"genre_scores_gemma":[0.01534029,0.0006447955,0.09094332,0.0005755639,0.0001321721,0.001039652,0.865363,0.01988602,0.006075283],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.0723521,"threshold_uncertainty_score":0.2420419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04047079739374036,"score_gpt":0.3415653462837238,"score_spread":0.3010945488899834,"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."}}