{"id":"W4391772262","doi":"10.1101/2024.02.11.24302646","title":"Diagnosing missed cases of spinal muscular atrophy in genome, exome, and panel sequencing datasets","year":2024,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Neurogenetic and Muscular Disorders Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Ottawa Hospital; Children's Hospital of Eastern Ontario","funders":"Medical Research Council; Canadian Institutes of Health Research; National Institutes of Health; Canada First Research Excellence Fund; Ataxia UK; National Institute of Neurological Disorders and Stroke; National Institute for Health and Care Research; UK Research and Innovation; Eesti Teadusagentuur; Government of Canada; LifeArc; National Human Genome Research Institute; HORIZON EUROPE Framework Programme; Department of Health and Social Care; NIHR Cambridge Biomedical Research Centre; Silicon Valley Community Foundation","keywords":"Spinal muscular atrophy; Exome sequencing; Exome; Medicine; Atrophy; Physical medicine and rehabilitation; Bioinformatics; Computational biology; Pathology; Genetics; Biology; Gene; Mutation; Disease","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":[0.006183702,0.001227386,0.001019408,0.003214395,0.001049253,0.00139366,0.001342311,0.002026835,0.002387922],"category_scores_gemma":[0.01914954,0.0003998879,0.00106392,0.001759491,0.0004394441,0.0007405649,0.002270365,0.001119979,0.001172542],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005181251,"about_ca_system_score_gemma":0.0007708957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002919723,"about_ca_topic_score_gemma":0.007550678,"domain_scores_codex":[0.9938062,0.00159142,0.0006926332,0.002693394,0.0007778184,0.000438567],"domain_scores_gemma":[0.989262,0.006390768,0.001227775,0.001495956,0.001150585,0.0004728431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001730917,0.0002282738,0.8432674,0.001348453,0.002346547,0.005280601,0.0006683449,0.01145284,0.04378148,0.0009933554,0.0346465,0.05425509],"study_design_scores_gemma":[0.0004078087,0.0004989216,0.7505621,0.000784467,0.001742143,0.01090836,0.001126329,0.1319437,0.04043978,0.005872224,0.05556149,0.0001528205],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8873829,0.003527206,0.04500361,0.0009102333,0.0003216264,0.0003012434,0.0579197,0.002566127,0.002067311],"genre_scores_gemma":[0.8047903,0.0004787154,0.05841666,0.001123219,0.0001228811,0.0003602825,0.133304,0.0003493979,0.001054449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006183702,"threshold_uncertainty_score":0.03270292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09373110980975002,"score_gpt":0.3410545946579789,"score_spread":0.2473234848482289,"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."}}