{"id":"W4401822209","doi":"10.1016/j.xhgg.2024.100344","title":"The performance of AlphaMissense to identify genes influencing disease","year":2024,"lang":"en","type":"article","venue":"Human Genetics and Genomics Advances","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University; Jewish General Hospital","funders":"Medical Research Council; Fonds de Recherche du Québec - Santé; National Institutes of Health; Fondation de l'Hôpital général juif; Medical Research Council Canada; Public Health Agency; European Commission; TD Bank; King's College London; Jewish General Hospital; National Institute for Health and Care Research; Wellcome Trust; Canada Foundation for Innovation; Génome Québec; Public Health Agency of Canada; McGill University; Canadian Institutes of Health Research; Compute Canada; Japan Society for the Promotion of Science; Cancer Research UK","keywords":"Gene; Genetics; Biology; Disease; Computational biology; Evolutionary biology; Medicine; Internal medicine","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":[0.006941349,0.001372404,0.001314941,0.002792463,0.0007878919,0.002054022,0.001078222,0.001582809,0.001697466],"category_scores_gemma":[0.0131545,0.0004148865,0.00176796,0.001211251,0.0006138582,0.0013461,0.001346992,0.001142409,0.000874534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004061216,"about_ca_system_score_gemma":0.0009226697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001599227,"about_ca_topic_score_gemma":0.002053495,"domain_scores_codex":[0.9972868,0.0009012127,0.0002710715,0.0007769721,0.000543499,0.0002203827],"domain_scores_gemma":[0.9862135,0.0107246,0.0008459154,0.0009308646,0.0009439006,0.0003412417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008009554,0.000730223,0.4184628,0.0006654414,0.002182417,0.0009318866,0.0006150455,0.1156076,0.04821198,0.003268,0.007582644,0.3937324],"study_design_scores_gemma":[0.000394532,0.002033308,0.06144328,0.0001020448,0.0004746161,0.002372869,0.0002568935,0.8946515,0.0242603,0.008164998,0.005721276,0.0001244898],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9002995,0.00252988,0.0865335,0.0007075354,0.0002035391,0.0001180834,0.001621943,0.004310071,0.003675918],"genre_scores_gemma":[0.9151149,0.0003691598,0.07890438,0.0003646128,0.00009370046,0.00009846413,0.003578989,0.0002528383,0.001222873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006941349,"threshold_uncertainty_score":0.03670979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007771629180966091,"score_gpt":0.2840540544750202,"score_spread":0.2762824252940542,"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."}}