{"id":"W2951924080","doi":"10.1371/journal.pgen.1007285","title":"Global characterization of copy number variants in epilepsy patients from whole genome sequencing","year":2018,"lang":"en","type":"article","venue":"PLoS Genetics","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":54,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University and Génome Québec Innovation Centre; Hospital for Sick Children; Centre Hospitalier Universitaire Sainte-Justine; Toronto Western Hospital; BC Children's Hospital; Montreal Neurological Institute and Hospital; University of Toronto; Université du Québec à Chicoutimi; Centre Hospitalier de l’Université de Montréal; McGill University; Ontario Genomics","funders":"Canadian Institutes of Health Research; Fonds de Recherche du Québec - Santé; Compute Canada; Genome Canada","keywords":"Copy-number variation; Epilepsy; Biology; Genetics; Genome; Gene; Whole genome sequencing; Computational biology; Coding region; Neuroscience","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":[0.000384317,0.0003432969,0.0004274509,0.001631824,0.00018916,0.0003553629,0.0002137045,0.0003158161,0.001540651],"category_scores_gemma":[0.001480081,0.0001042203,0.0003851315,0.0009811008,0.0002192051,0.0001478192,0.0004461966,0.0002295433,0.0001972369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001215891,"about_ca_system_score_gemma":0.0001300794,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001257858,"about_ca_topic_score_gemma":0.002233641,"domain_scores_codex":[0.999644,0.00005096836,0.00003914386,0.0001511381,0.00007308726,0.00004171255],"domain_scores_gemma":[0.9996365,0.0001634326,0.00007842488,0.00005239726,0.00003363423,0.00003565279],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004494851,0.00004775282,0.7784325,0.0001404187,0.0004747549,0.003451835,0.0004582798,0.001438686,0.1491703,0.0005649203,0.000785335,0.06458565],"study_design_scores_gemma":[0.00002642664,0.000147759,0.9774874,0.00001837306,0.0001486031,0.005155453,0.0001458737,0.002136484,0.01149792,0.0006951464,0.002522373,0.0000181935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9930715,0.0005328,0.004215551,0.00004772994,0.000006284891,0.00003222909,0.001412541,0.00005799504,0.000623418],"genre_scores_gemma":[0.9930239,0.000349442,0.002982721,0.00005390395,0.00001019769,0.00003981639,0.003115282,0.00002618894,0.0003985527],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001631824,"threshold_uncertainty_score":0.005154014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01013067397027378,"score_gpt":0.2169110716504071,"score_spread":0.2067803976801333,"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."}}