{"id":"W4411754998","doi":"10.1093/nargab/lqaf087","title":"MOLGENIS VIP: an end-to-end DNA variant interpretation pipeline for research and diagnostics configurable to support rapid implementation of new methods","year":2025,"lang":"en","type":"article","venue":"NAR Genomics and Bioinformatics","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Nederlandse Organisatie voor Wetenschappelijk Onderzoek","keywords":"Scalability; Pipeline (software); Computer science; Data science; DNA sequencing; Genome; Variety (cybernetics); Software; Protocol (science); Computational biology; Data mining; Biology; Medicine; Artificial intelligence; Genetics; Database; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005949493,0.002691091,0.001737502,0.003300498,0.001371124,0.003576785,0.003115993,0.001966795,0.0221151],"category_scores_gemma":[0.01128068,0.002306021,0.002313394,0.002623398,0.001097578,0.002326436,0.004942333,0.004032355,0.02062496],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001037132,"about_ca_system_score_gemma":0.00302635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002358767,"about_ca_topic_score_gemma":0.003013035,"domain_scores_codex":[0.9972645,0.0004527934,0.0002221153,0.001154244,0.0006894731,0.0002168562],"domain_scores_gemma":[0.9952623,0.001941254,0.0006315327,0.0009701988,0.0006550088,0.00053966],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.006194124,0.0003324404,0.02501819,0.004232705,0.001591651,0.002095535,0.002102511,0.01247895,0.1346776,0.01119629,0.4956569,0.3044231],"study_design_scores_gemma":[0.001729458,0.0009344955,0.03540522,0.0009780632,0.0006010621,0.00345266,0.0006093277,0.1276073,0.1884452,0.05305776,0.5862294,0.0009500947],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01358339,0.001201311,0.4916122,0.0008569147,0.0006433602,0.0008150819,0.07874364,0.4048232,0.007720886],"genre_scores_gemma":[0.05228916,0.0006845821,0.7283022,0.001534015,0.000250436,0.001524589,0.1663368,0.043561,0.005517303],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0221151,"threshold_uncertainty_score":0.07398242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04216451958384585,"score_gpt":0.3995709628316272,"score_spread":0.3574064432477814,"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."}}