{"id":"W4238285403","doi":"10.1038/s41436-021-01278-8","title":"Correction to: ACMG SF v3.0 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG)","year":2021,"lang":"en","type":"erratum","venue":"Genetics in Medicine","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Institutes of Health","keywords":"Medical genetics; Exome sequencing; Statement (logic); Genomics; Exome; Computational biology; Medicine; Genome; Genetics; Biology; Mutation; Gene; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006524465,0.001782691,0.001607871,0.003902476,0.003123709,0.004293482,0.002811099,0.006818829,0.09895667],"category_scores_gemma":[0.09840067,0.001182439,0.001481471,0.002586688,0.002237955,0.002246576,0.002285482,0.0128017,0.07487485],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003401893,"about_ca_system_score_gemma":0.00684147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02720951,"about_ca_topic_score_gemma":0.03085529,"domain_scores_codex":[0.9940284,0.0010742,0.001247058,0.0006430596,0.002547134,0.0004601063],"domain_scores_gemma":[0.9508266,0.01715248,0.002316857,0.002537846,0.0252757,0.001890551],"domain_codex":null,"domain_gemma":"reporting","domain_candidate":"reporting","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001058099,0.000002103297,0.00003275553,0.00002895477,0.000002230926,0.00006850604,0.000008915556,0.00001065558,0.000009249895,0.0002481376,0.9976398,0.00193813],"study_design_scores_gemma":[0.00004137749,0.00001006858,0.0005465172,0.0003609517,0.0000167875,0.000414489,0.00005391287,0.0001155765,0.0001463748,0.001496506,0.9967694,0.00002804278],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001544665,0.0006637668,0.001270458,0.1191498,0.8645927,0.00006433506,0.005723119,0.000955656,0.007425606],"genre_scores_gemma":[0.008773378,0.004693107,0.0107282,0.3009102,0.2950402,0.000608334,0.01200369,0.004738788,0.3625042],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.9934756,"threshold_uncertainty_score":0.3310431,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03557889635643506,"score_gpt":0.3684972766173683,"score_spread":0.3329183802609332,"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."}}