{"id":"W7045233164","doi":"","title":"Adult genetic leukoencephalopathies: identifying new entities using advanced MRI techniques, next generation sequencing and clinical profiling","year":2019,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"RNA regulation and disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de Recherche du Québec - Santé; Bundesministerium für Bildung und Forschung; ZonMw; Ontario Genomics Institute; Canadian Institutes of Health Research; McGill University Health Centre; Genome Canada; Ontario Genomics; Children's Hospital Foundation; American Society of Neuroradiology; McGill University","keywords":"White matter; Exome sequencing; Leukoencephalopathy; Genetic testing; Phenotype; Neuroimaging; Genetic heterogeneity; Magnetic resonance imaging","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001308783,0.0003844163,0.0004335573,0.002068009,0.0002259414,0.0007576943,0.0003175842,0.0004886411,0.0007499201],"category_scores_gemma":[0.001366187,0.0001377773,0.0001900398,0.001453886,0.00035752,0.0005758565,0.0006370234,0.0004039772,0.0003535353],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001897444,"about_ca_system_score_gemma":0.0002435698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001233472,"about_ca_topic_score_gemma":0.001396204,"domain_scores_codex":[0.9994428,0.000137287,0.00007144506,0.0001563413,0.0001508435,0.00004124455],"domain_scores_gemma":[0.9994729,0.0001430313,0.000158914,0.00005707002,0.0001105389,0.00005746324],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003903634,0.0001341529,0.7449771,0.000297556,0.00009890843,0.005323714,0.0008349884,0.0007797979,0.08076937,0.001162398,0.001677157,0.1635545],"study_design_scores_gemma":[0.00002544403,0.0003259136,0.9314094,0.0002064176,0.0001559674,0.02331249,0.000674551,0.006401445,0.01566259,0.002810261,0.01897339,0.00004215505],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9462658,0.01522519,0.03214808,0.0009349741,0.00005992694,0.0002067441,0.001757371,0.0002010045,0.003200985],"genre_scores_gemma":[0.9247203,0.01399767,0.05714766,0.0006944349,0.0002486603,0.0001591702,0.001797116,0.00003501544,0.001199873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002068009,"threshold_uncertainty_score":0.006921589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04834810870336882,"score_gpt":0.3081657239666637,"score_spread":0.2598176152632949,"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."}}