{"id":"W2095208613","doi":"10.1089/hum.2008.162","title":"Efficient and Fast Functional Screening of Microdystrophin Constructs <i>In Vivo</i> and <i>In Vitro</i> for Therapy of Duchenne Muscular Dystrophy","year":2009,"lang":"en","type":"article","venue":"Human Gene Therapy","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Duchenne muscular dystrophy; Dystrophin; Exon skipping; Muscular dystrophy; Genetic enhancement; In silico; Transgene; Biology; Computational biology; Exon; In vivo; Gene; In vitro; Bioinformatics; Genetics; Alternative splicing","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0007216803,0.0006362576,0.0003890568,0.000358463,0.0001725865,0.0004063729,0.000326688,0.0004629507,0.001194919],"category_scores_gemma":[0.0004919654,0.0002358516,0.0003947005,0.0001803474,0.0002683879,0.0002154006,0.0003112731,0.0004888582,0.0008216845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002577532,"about_ca_system_score_gemma":0.0001542396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002641117,"about_ca_topic_score_gemma":0.0004740989,"domain_scores_codex":[0.9993953,0.0001938781,0.00006493272,0.00009727247,0.0001837054,0.00006498166],"domain_scores_gemma":[0.9995477,0.0002071263,0.00008425547,0.00006665245,0.00005085785,0.00004338241],"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":[0.0000196318,0.00001347367,0.00003756875,0.00001897992,0.000002368983,0.00001389727,0.000006950647,0.00008582048,0.99892,0.00004690128,0.00001947124,0.0008150353],"study_design_scores_gemma":[0.00000331338,0.00009524288,0.0003278416,0.000002191172,0.00000562551,0.00006407814,0.000005701959,0.0003403073,0.9984512,0.00001665265,0.0006843053,0.000003458083],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8732028,0.004904183,0.1143658,0.0002921663,0.0001066007,0.000396575,0.002036182,0.0005558084,0.0041399],"genre_scores_gemma":[0.9107275,0.003743875,0.07482239,0.0001210485,0.00002329685,0.0003228919,0.004110795,0.0002243447,0.005903815],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001194919,"threshold_uncertainty_score":0.003997445,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117491474215175,"score_gpt":0.2323797598550573,"score_spread":0.2206306124335398,"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."}}