{"id":"W2900564760","doi":"10.3390/jpm8040038","title":"Applications of CRISPR/Cas9 for the Treatment of Duchenne Muscular Dystrophy","year":2018,"lang":"en","type":"review","venue":"Journal of Personalized Medicine","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":73,"is_retracted":false,"has_abstract":true,"ca_institutions":"Muscular Dystrophy Canada; University of Alberta","funders":"Canadian Institutes of Health Research","keywords":"CRISPR; Genome editing; Duchenne muscular dystrophy; Dystrophin; Cas9; Exon skipping; Medicine; Muscular dystrophy; Genetic enhancement; Bioinformatics; Computational biology; Biology; Genetics; Gene; Exon; 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":[],"consensus_categories":[],"category_scores_codex":[0.0003335647,0.0002287462,0.001100521,0.0001065042,0.00003302082,0.000002453019,0.0002630932,0.0001563458,0.00003736957],"category_scores_gemma":[0.00009986585,0.0001206044,0.0008055003,0.0001201882,0.0002233408,0.000001205284,0.00001506491,0.00007468204,4.281638e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003015063,"about_ca_system_score_gemma":0.0001727489,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007748079,"about_ca_topic_score_gemma":0.000001691688,"domain_scores_codex":[0.9987012,0.00003793186,0.0007677861,0.0001538994,0.0002031067,0.0001360617],"domain_scores_gemma":[0.9982812,0.0001138964,0.0007888441,0.0003410736,0.0003969053,0.00007801546],"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":[0.0002083165,0.000374659,0.000003066072,0.01051946,0.003766171,0.000005070337,0.0005029688,0.00001766822,0.00839522,0.00009928739,0.006979886,0.9691283],"study_design_scores_gemma":[0.00120297,0.002255689,0.000001655606,0.001401917,0.002749165,0.0001024625,0.0001252363,0.000005494832,0.001231591,0.00001030795,0.9908214,0.00009210967],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006178042,0.9339568,0.06501067,0.00008600776,0.0002185533,0.0005872168,0.00005220145,0.000001095193,0.00002565034],"genre_scores_gemma":[0.0001841873,0.9954994,0.001684646,0.00001171956,0.002145933,0.00007502283,0.0000490221,0.00003023312,0.0003198333],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9838415,"threshold_uncertainty_score":0.4918104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03045498754806557,"score_gpt":0.4020737553894709,"score_spread":0.3716187678414053,"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."}}