{"id":"W4388968103","doi":"10.1016/j.jmoldx.2023.11.002","title":"Variant Classification Discordance","year":2023,"lang":"en","type":"article","venue":"Journal of Molecular Diagnostics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Mitacs; Queen's University","keywords":"Computer science; Classifier (UML); Allele; Precision and recall; Computational biology; Artificial intelligence; Gene; Genetics; Biology","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":[0.01732942,0.001168341,0.002309175,0.01290944,0.001262511,0.005134735,0.002261782,0.001175354,0.006673232],"category_scores_gemma":[0.06711329,0.0004567376,0.001684968,0.008081264,0.0009122846,0.001679088,0.003042122,0.001389559,0.003683473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001111372,"about_ca_system_score_gemma":0.001613828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002381681,"about_ca_topic_score_gemma":0.002769474,"domain_scores_codex":[0.9689161,0.005296527,0.007112923,0.007075293,0.0104689,0.001130176],"domain_scores_gemma":[0.9371063,0.02689076,0.008920032,0.01245017,0.01332008,0.001312614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002697045,0.000195112,0.4920828,0.001544595,0.001174997,0.0019246,0.001298222,0.003372753,0.009826258,0.004600947,0.07230339,0.4089793],"study_design_scores_gemma":[0.000485101,0.0006962449,0.5007785,0.001491022,0.002210439,0.02142892,0.002106558,0.08522184,0.06171137,0.0335892,0.2896333,0.0006475071],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6017641,0.0171566,0.2031338,0.001901688,0.003424518,0.002279744,0.1185274,0.01700373,0.03480846],"genre_scores_gemma":[0.8037972,0.00185177,0.0797104,0.0009710778,0.0007025034,0.0007260229,0.1034382,0.001699824,0.007103019],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01732942,"threshold_uncertainty_score":0.09164774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01153488621322834,"score_gpt":0.2577990208295927,"score_spread":0.2462641346163644,"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."}}