{"id":"W3045297762","doi":"10.1002/ajmg.a.61724","title":"Genotype–phenotype correlation at codon 1740 of <scp><i>SETD2</i></scp>","year":2020,"lang":"en","type":"article","venue":"American Journal of Medical Genetics Part A","topic":"Epigenetics and DNA Methylation","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Medical Research Council; Department of Health and Aged Care, Australian Government; Deutsche Forschungsgemeinschaft; National Institute for Health and Care Research; Department of Health and Social Care; Cancer Research UK; Wellcome Trust","keywords":"Genetics; Biology; Missense mutation; Histone methyltransferase; Microcephaly; Histone H3; Phenotype; Histone; Methyltransferase; Histone methylation; Epigenetics; Gene; Methylation; DNA methylation; Gene expression","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":[],"consensus_categories":[],"category_scores_codex":[0.0002465986,0.0006773323,0.0003361015,0.0007506129,0.0003969001,0.0003066562,0.000233606,0.0005961424,0.004034256],"category_scores_gemma":[0.000933059,0.0001601034,0.0003000626,0.0005182138,0.0003526624,0.0001346077,0.0002674458,0.000452749,0.0003934899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001736155,"about_ca_system_score_gemma":0.0001694844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001949257,"about_ca_topic_score_gemma":0.001250778,"domain_scores_codex":[0.9995764,0.00007033567,0.00004926789,0.0001753307,0.00007294813,0.00005577419],"domain_scores_gemma":[0.9992513,0.000291751,0.0001893885,0.00004177847,0.0000676478,0.0001580696],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00139797,0.0003344833,0.861424,0.00004826107,0.0002466024,0.02870687,0.0005209642,0.000565099,0.09518864,0.000418282,0.0009569765,0.01019186],"study_design_scores_gemma":[0.00006141231,0.000781916,0.942444,0.00001242138,0.0001010173,0.0478834,0.0001425029,0.001085258,0.005878848,0.0001800071,0.001401132,0.00002814287],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985777,0.00006704528,0.0002700281,0.00004398522,0.00001253134,0.00001273276,0.0002704253,0.00001070857,0.0007348532],"genre_scores_gemma":[0.9989753,0.00002569694,0.000250935,0.00003515341,0.00001183884,0.000008789535,0.0002965683,0.000007520533,0.0003882287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004034256,"threshold_uncertainty_score":0.01349592,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411500433248008,"score_gpt":0.2640159103564816,"score_spread":0.2499009060240015,"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."}}