{"id":"W2005611432","doi":"10.1038/ejhg.2013.132","title":"Clinical utility gene card for: Beckwith–Wiedemann Syndrome","year":2013,"lang":"en","type":"article","venue":"European Journal of Human Genetics","topic":"Genetic Syndromes and Imprinting","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":false,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"National Institute of General Medical Sciences; Instituto de Salud Carlos III; Agence Nationale de la Recherche; Assistance publique-Hôpitaux de Paris; Bundesministerium für Bildung und Forschung; Institut National de la Santé et de la Recherche Médicale; Action Medical Research","keywords":"Beckwith–Wiedemann syndrome; Genetics; Gene; Medicine; Biology; Computational biology; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001433001,0.0002209046,0.0003548161,0.00006190467,0.0001395482,0.00007506351,0.000569407,0.00008283263,0.00006325622],"category_scores_gemma":[0.0001382941,0.0001976524,0.0004285453,0.00005035569,0.0001391278,0.000005681563,0.0002206939,0.0002005999,0.00004711264],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008614865,"about_ca_system_score_gemma":0.00006223225,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001836008,"about_ca_topic_score_gemma":0.00000155606,"domain_scores_codex":[0.9976484,0.0003456424,0.001106545,0.0003234054,0.0002180651,0.000357953],"domain_scores_gemma":[0.9982198,0.00002237097,0.0005428196,0.0005161813,0.0004382749,0.000260507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005530685,0.0006727798,0.1523027,0.0001367103,0.001051428,0.0001292875,0.0002935072,0.0002753141,0.7004808,0.00003226693,0.04172979,0.1028401],"study_design_scores_gemma":[0.002460961,0.006916416,0.8967501,0.00005972135,0.0001678421,0.001433555,0.0001896632,0.0001118374,0.01932334,0.0002285191,0.07181548,0.0005425664],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9909415,0.001639399,0.005035706,0.00007707612,0.0005606191,0.0002524717,0.000007578534,0.000006845183,0.001478828],"genre_scores_gemma":[0.9841822,0.000258915,0.01376521,0.000187573,0.0008585276,0.000002696679,0.00001687676,0.00006649467,0.0006614376],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7444474,"threshold_uncertainty_score":0.8060032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.038195041901473,"score_gpt":0.3009586668574965,"score_spread":0.2627636249560235,"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."}}