{"id":"W2798099534","doi":"10.1101/199224","title":"Global characterization of copy number variants in epilepsy patients from whole genome sequencing","year":2017,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Centre Hospitalier Universitaire Sainte-Justine; McGill University and Génome Québec Innovation Centre; Hospital for Sick Children; Toronto Western 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":"Compute Canada; Genome Canada","keywords":"Epilepsy; Copy-number variation; Genome; Gene; Genetics; Biology; Coding region; Whole genome sequencing; Computational biology; 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":[0.0002815916,0.0002287465,0.0002870199,0.001335526,0.0001406405,0.0002744505,0.0001832199,0.0002340581,0.001996376],"category_scores_gemma":[0.001046488,0.00007848652,0.0002701243,0.0007021878,0.0001383869,0.0001186024,0.0003208089,0.0001508558,0.0002154439],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009682819,"about_ca_system_score_gemma":0.00008999056,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009601323,"about_ca_topic_score_gemma":0.001392788,"domain_scores_codex":[0.9997995,0.0000310013,0.00002758996,0.00007747713,0.00004089121,0.00002356521],"domain_scores_gemma":[0.9996666,0.0001422268,0.00007530975,0.00003875464,0.00004260319,0.0000344846],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000384436,0.00002958056,0.8978831,0.00005938771,0.000236977,0.001857805,0.0001618192,0.0007062517,0.0711036,0.0001693582,0.0005229257,0.02688474],"study_design_scores_gemma":[0.00001625018,0.000103245,0.9873955,0.000008677969,0.00009065687,0.003523316,0.00009663038,0.001278713,0.006169182,0.000243954,0.001064829,0.000009088537],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9967805,0.0002634987,0.001326509,0.00002494952,0.00000323716,0.00001530578,0.001151261,0.00002790019,0.0004069003],"genre_scores_gemma":[0.9962215,0.0001218524,0.001154048,0.00002756399,0.000005119388,0.00001573836,0.002171797,0.00001110367,0.0002712389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001996376,"threshold_uncertainty_score":0.006678522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009146324993468073,"score_gpt":0.2102369202476752,"score_spread":0.2010905952542072,"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."}}