{"id":"W4220970247","doi":"10.1093/bioinformatics/btac157","title":"RevUP: an online scoring system for regulatory variants implicated in rare diseases","year":2022,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; University of British Columbia","funders":"ZonMw","keywords":"Classifier (UML); Computer science; Source code; Scoring system; Phenotype; Data mining; Computational biology; Artificial intelligence; Biology; Genetics; Medicine; 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":[0.007014542,0.001959102,0.00139645,0.006065218,0.001111754,0.002627966,0.00294362,0.001583148,0.04469262],"category_scores_gemma":[0.03578253,0.001082354,0.001999831,0.002929316,0.0004907114,0.001871999,0.003405117,0.001604544,0.02162146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008178525,"about_ca_system_score_gemma":0.002036996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001913126,"about_ca_topic_score_gemma":0.003637874,"domain_scores_codex":[0.995281,0.001232457,0.0007767939,0.001234328,0.001220181,0.0002552562],"domain_scores_gemma":[0.9885918,0.006864068,0.001132069,0.001086554,0.00197313,0.0003523737],"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":[0.001961979,0.0002225424,0.05370598,0.003836048,0.0008435323,0.001854763,0.0005226564,0.01012378,0.01573385,0.008290717,0.4391979,0.4637062],"study_design_scores_gemma":[0.001676945,0.0007159089,0.07313311,0.002042682,0.001368891,0.0127227,0.0005447528,0.2290466,0.06627482,0.0674052,0.5441051,0.0009632294],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04754947,0.002799502,0.5449449,0.001908222,0.001058894,0.001374832,0.1445815,0.2428857,0.01289691],"genre_scores_gemma":[0.1791067,0.001168918,0.6266244,0.001248735,0.0004782981,0.002233105,0.1471892,0.03193571,0.01001494],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04469262,"threshold_uncertainty_score":0.1495116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726970244398393,"score_gpt":0.2424494757252676,"score_spread":0.2251797732812837,"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."}}