{"id":"W4317655863","doi":"10.1101/2023.01.20.524978","title":"Base editing as a genetic treatment for spinal muscular atrophy","year":2023,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Neurogenetic and Muscular Disorders Research","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"Canadian Institutes of Health Research; National Institutes of Health; Muscular Dystrophy Canada; Charles A. King Trust; St. Jude Children's Research Hospital; Massachusetts General Hospital; Muscular Dystrophy Association","keywords":"SMN1; Spinal muscular atrophy; Exon; SMA*; Genome editing; Biology; Mutation; Genetics; Gene; Translation (biology); CRISPR; Messenger RNA; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000390858,0.0007072997,0.0008852286,0.0004732538,0.0002344972,0.000143103,0.0003606219,0.000488617,0.00006777098],"category_scores_gemma":[0.0004077033,0.0006933836,0.0007387248,0.0004589802,0.0001502005,0.00003626243,0.0003775568,0.0005614915,0.0002786639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004199368,"about_ca_system_score_gemma":0.001531848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001603471,"about_ca_topic_score_gemma":0.000003661863,"domain_scores_codex":[0.9960291,0.0001239361,0.0005937918,0.001509799,0.0007469147,0.0009963969],"domain_scores_gemma":[0.9967861,0.00006936257,0.0002348664,0.001671078,0.0005991213,0.0006395424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001127235,0.001642977,0.01387119,0.006550087,0.002985151,0.003687271,0.00003361003,0.0003411348,0.9671146,0.0005104902,0.001846962,0.0002892771],"study_design_scores_gemma":[0.01762829,0.00853233,0.331303,0.004094274,0.004566681,0.000001314304,0.00006828954,0.00592526,0.5444804,0.00004621873,0.07971633,0.00363762],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9853824,0.003503998,0.003995645,0.001069085,0.001182101,0.004110424,0.0002116154,0.000532843,0.00001191089],"genre_scores_gemma":[0.9802806,0.001401315,0.01300515,0.0003192984,0.002058052,0.002437577,0.000002651265,0.0004212976,0.00007409459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4226342,"threshold_uncertainty_score":0.9995517,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04280534822212803,"score_gpt":0.3003664318143692,"score_spread":0.2575610835922412,"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."}}