{"id":"W2987965949","doi":"10.1186/s13059-019-1845-6","title":"MaveDB: an open-source platform to distribute and interpret data from multiplexed assays of variant effect","year":2019,"lang":"en","type":"article","venue":"Genome biology","topic":"Evolution and Genetic Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":279,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; Sinai Health System; Lunenfeld-Tanenbaum Research Institute; Muscular Dystrophy Canada; University of Toronto","funders":"Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; National Health and Medical Research Council; Lorenzo and Pamela Galli Charitable Trust; Australian Government; University of Washington","keywords":"Biology; Computational biology; Multiplex; Interoperability; Human genetics; Sequence (biology); Computer science; Resource (disambiguation); Open source; Data mining; Data science; Information retrieval; Bioinformatics; Genetics; World Wide Web; Software; Gene","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":["open_science"],"consensus_categories":[],"category_scores_codex":[0.005115309,0.002783454,0.002850938,0.006826321,0.001445944,0.005793162,0.005833245,0.002493392,0.02339163],"category_scores_gemma":[0.01605634,0.002583101,0.002436369,0.005459824,0.0009023623,0.00339051,0.007120407,0.004058291,0.02556265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001150933,"about_ca_system_score_gemma":0.003012696,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00526211,"about_ca_topic_score_gemma":0.00939768,"domain_scores_codex":[0.9968454,0.0004191383,0.0003661416,0.000874261,0.00124757,0.0002474933],"domain_scores_gemma":[0.9944528,0.001676184,0.0007290049,0.001857242,0.0007066097,0.0005781915],"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":[0.003885746,0.0004574118,0.02841474,0.004385744,0.002324728,0.001091157,0.0007918568,0.006910632,0.04330336,0.01388287,0.7859275,0.1086243],"study_design_scores_gemma":[0.001101683,0.0002079591,0.02139505,0.000748986,0.0004902769,0.001395741,0.0002601741,0.04244338,0.05510523,0.04500843,0.8312145,0.0006286143],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.008534669,0.002560641,0.1407121,0.0009588637,0.0006286008,0.0003957305,0.4573947,0.380727,0.008087701],"genre_scores_gemma":[0.03802283,0.001711706,0.1688357,0.001404588,0.000195022,0.001639822,0.7258199,0.0562917,0.006078849],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.9941667,"threshold_uncertainty_score":0.07825279,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01686326545011065,"score_gpt":0.2893639845814499,"score_spread":0.2725007191313392,"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."}}