{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001807226,0.00009035454,0.0001101814,0.00007275652,0.00003962751,0.00002690509,0.000198591,0.00006216048,0.000005076123],"category_scores_gemma":[0.0006330774,0.00007953995,0.0001319122,0.0001389,0.00003495717,0.000003016189,0.00005944364,0.00007388512,0.00002067612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009864599,"about_ca_system_score_gemma":0.0001116003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":9.221263e-7,"about_ca_topic_score_gemma":0.000001330366,"domain_scores_codex":[0.9992686,0.00003911173,0.0002573692,0.0001195116,0.0001652098,0.000150217],"domain_scores_gemma":[0.9992911,0.00003201339,0.0001969497,0.0002041897,0.0001730214,0.0001027635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007487377,0.0001688904,0.004226676,0.0000263826,0.00015072,0.001055984,0.00003836826,0.001858445,0.9610106,0.001844694,0.02583064,0.003713702],"study_design_scores_gemma":[0.003724828,0.002415476,0.3434876,0.0002819228,0.0005569001,0.002007069,0.0007619496,0.001434003,0.4149487,0.009065915,0.219991,0.001324662],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9845146,0.001574796,0.01258065,0.0005174755,0.0004280423,0.00007058971,0.00002283065,0.000006374867,0.0002846321],"genre_scores_gemma":[0.9952259,0.003361225,0.0008136634,0.000206332,0.0002510545,0.000003242425,0.00005134766,0.00002003857,0.00006716032],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5460619,"threshold_uncertainty_score":0.3243545,"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."}}