{"id":"W3093402981","doi":"10.1101/2020.10.14.339499","title":"MaveRegistry: a collaboration platform for multiplexed assays of variant effect","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sinai Health System; Lunenfeld-Tanenbaum Research Institute; University of Toronto","funders":"National Institutes of Health; National Human Genome Research Institute; Canada Excellence Research Chairs, Government of Canada","keywords":"Multiplexing; Computational biology; NOMINATE; Computer science; Data science; Biology; Machine learning; Telecommunications","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":[0.01430903,0.001381452,0.001755284,0.003321872,0.0008497767,0.004112245,0.002909975,0.001567542,0.03623904],"category_scores_gemma":[0.02084585,0.001293855,0.001336457,0.001653904,0.0009246423,0.002965697,0.007973751,0.002924702,0.02249974],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006708094,"about_ca_system_score_gemma":0.002552649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001669036,"about_ca_topic_score_gemma":0.001757116,"domain_scores_codex":[0.9930295,0.002002176,0.00055965,0.001728052,0.002133434,0.000547189],"domain_scores_gemma":[0.9827341,0.006994004,0.001358371,0.005491508,0.001255077,0.00216695],"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":[0.005304849,0.0004304579,0.01429373,0.001123567,0.0009748399,0.001787052,0.001211561,0.009189939,0.0531772,0.0480565,0.5943626,0.2700877],"study_design_scores_gemma":[0.001836696,0.0004433744,0.01187843,0.0003613064,0.0002918847,0.001472292,0.000271156,0.06614731,0.07876404,0.1161528,0.7217383,0.0006424591],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01364191,0.0008935478,0.5869637,0.001846632,0.0007983751,0.0007630102,0.05898451,0.3205717,0.01553656],"genre_scores_gemma":[0.1428674,0.0009792724,0.630071,0.002039453,0.0007013444,0.004144162,0.1371688,0.06122616,0.0208025],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03623904,"threshold_uncertainty_score":0.1212316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117380581173875,"score_gpt":0.2278526144307381,"score_spread":0.2161145563133506,"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."}}