{"id":"W4313814066","doi":"10.20944/preprints202301.0139.v1","title":"Recent Trends in Antisense Therapies for Duchenne muscular dystrophy","year":2023,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Muscular Dystrophy Canada; Alberta Innovates; Alberta Innovates - Health Solutions; Women and Children's Health Research Institute; Children's Health Research Institute","keywords":"Duchenne muscular dystrophy; Antisense therapy; Exon skipping; Muscular dystrophy; Medicine; Disease; Clinical trial; Genetic enhancement; Dystrophin; Bioinformatics; Exon; Gene; Biology; Genetics; Internal medicine; Alternative splicing","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":[0.0004668845,0.0003992689,0.0004213323,0.0002564876,0.00005580844,0.00002643125,0.0005841609,0.0005525358,0.0001734955],"category_scores_gemma":[0.000154548,0.0004106079,0.000383401,0.0001523417,0.00007791995,0.000004209568,0.001135619,0.000371149,0.0001914319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005884422,"about_ca_system_score_gemma":0.0000996384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001689151,"about_ca_topic_score_gemma":0.0001993832,"domain_scores_codex":[0.9975426,0.000110491,0.0004860889,0.001238807,0.0001687011,0.0004533418],"domain_scores_gemma":[0.998216,0.00001795202,0.0001922009,0.00128288,0.00020044,0.00009049295],"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":[0.0005634179,0.0002840414,0.1180869,0.0001810902,0.0006753935,0.00004525556,0.0005579994,0.001440038,0.8590743,0.00004363478,0.001887644,0.01716028],"study_design_scores_gemma":[0.001429971,0.0002493293,0.3669296,0.00021798,0.000101377,0.00001052407,0.0002277578,0.0001845603,0.526965,0.001373231,0.1012277,0.001083039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995455,0.001700184,0.0001412381,0.0007373807,0.0009424668,0.0004694208,0.0001358722,0.00005695814,0.0003615147],"genre_scores_gemma":[0.9845837,0.009158393,0.0002260415,0.0001396218,0.00043339,0.0004102311,0.0009999387,0.00008153301,0.003967184],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3321093,"threshold_uncertainty_score":0.9998346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1353912280836743,"score_gpt":0.3615361751009483,"score_spread":0.2261449470172741,"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."}}