{"id":"W2280557044","doi":"10.1016/j.gendis.2016.02.001","title":"Gene editing: A new step and a new direction toward finding a cure for Duchenne muscular dystrophy (DMD)","year":2016,"lang":"en","type":"article","venue":"Genes & Diseases","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health; Cystic Fibrosis Canada; Canadian Institutes of Health Research; Hospital for Sick Children; National Institute of Neurological Disorders and Stroke; Cystic Fibrosis Foundation Therapeutics","keywords":"Duchenne muscular dystrophy; Dystrophin; Exon; Muscular dystrophy; Exon skipping; Gene; Muscle disease; Disease; Neuromuscular disease; Medicine; Genome editing; Bioinformatics; Genetic enhancement; Genetics; Biology; Internal medicine; Alternative splicing; CRISPR","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":[0.002010995,0.0006369815,0.001028499,0.0006297454,0.0005901792,0.00229515,0.0007730242,0.002135414,0.003144513],"category_scores_gemma":[0.001481467,0.0002648828,0.0006126174,0.0002883913,0.002553109,0.004098195,0.001342483,0.005187985,0.001094128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008045305,"about_ca_system_score_gemma":0.0007806784,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004157109,"about_ca_topic_score_gemma":0.0006023509,"domain_scores_codex":[0.9992769,0.0001400962,0.00004429825,0.0001605907,0.0002778552,0.0001001733],"domain_scores_gemma":[0.9990413,0.0004078607,0.00009923579,0.00009587309,0.0001664485,0.0001892332],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0007256722,0.0003445303,0.001391589,0.002653046,0.000221712,0.001824282,0.0009635766,0.0008908832,0.1443461,0.1611468,0.09034689,0.5951449],"study_design_scores_gemma":[0.0001671168,0.001104337,0.001013498,0.0009009728,0.0001773769,0.003743214,0.0005031936,0.001276961,0.04471583,0.05458791,0.8916945,0.000115121],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.02657054,0.718531,0.07859277,0.1416323,0.0124912,0.0001226054,0.0003104712,0.001124164,0.02062506],"genre_scores_gemma":[0.1760566,0.6632353,0.07146627,0.04816927,0.007200222,0.0002336655,0.0006091162,0.0004040239,0.03262552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003144513,"threshold_uncertainty_score":0.01063532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334731338699647,"score_gpt":0.2782902035300337,"score_spread":0.2649428901430372,"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."}}