{"id":"W4416341184","doi":"10.20944/preprints202511.1240.v1","title":"From Genomic Diagnosis to Personalized RNA Medicine: Advances in Next-Generation Sequencing and N-of-1 Antisense Oligonucleotide Therapies for Rare Genetic Diseases","year":2025,"lang":"","type":"preprint","venue":"Preprints.org","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Faculty of Medicine and Dentistry, University of Alberta; Canadian Institutes of Health Research; Muscular Dystrophy Canada; University of Alberta; Alberta Innovates - Health Solutions; Women and Children's Health Research Institute; Children's Health Research Institute; Alberta Innovates; Heart and Stroke Foundation of Canada; U.S. Department of Defense","keywords":"Personalized medicine; Oligonucleotide; RNA; RNA splicing; Morpholino; Genome; DNA sequencing; Precision medicine","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":[0.001822752,0.0005964553,0.0007337813,0.0008993355,0.0003156785,0.001381848,0.000582803,0.001237516,0.002882841],"category_scores_gemma":[0.001812713,0.0002988076,0.0006269311,0.0005739158,0.0009613384,0.00237446,0.001033991,0.002632766,0.001003222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000770364,"about_ca_system_score_gemma":0.001054313,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007152676,"about_ca_topic_score_gemma":0.001462529,"domain_scores_codex":[0.9993078,0.0002314781,0.00006064437,0.0001321297,0.0002155378,0.00005249524],"domain_scores_gemma":[0.9991048,0.0006407732,0.00005817209,0.00002720603,0.0001173567,0.00005177076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001681575,0.00009263719,0.0007524734,0.006877524,0.0001207634,0.0007137873,0.0005043083,0.002157525,0.03147486,0.05675015,0.03211473,0.868273],"study_design_scores_gemma":[0.00002844575,0.0002875229,0.0007013477,0.002401927,0.0001085912,0.002173123,0.0002328589,0.002564911,0.01202238,0.03024078,0.9491552,0.00008294973],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002795903,0.9482997,0.02616697,0.01331504,0.002201012,0.00003630317,0.00009696035,0.0001943399,0.00689383],"genre_scores_gemma":[0.01672371,0.9510193,0.01983765,0.006747969,0.002269638,0.00006178269,0.0001565387,0.00005219506,0.003131168],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.002882841,"threshold_uncertainty_score":0.009644032,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08048142760275755,"score_gpt":0.3319674452225216,"score_spread":0.2514860176197641,"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."}}