{"id":"W2889188774","doi":"10.1007/978-1-4939-8651-4_36","title":"Exon Skipping Using Antisense Oligonucleotides for Laminin-Alpha2-Deficient Muscular Dystrophy","year":2018,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Muscle Physiology and Disorders","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Nippon Shinyaku; National Center of Neurology and Psychiatry; Sarepta Therapeutics; Japan Agency for Medical Research and Development","keywords":"Laminin; Duchenne muscular dystrophy; Myogenesis; Congenital muscular dystrophy; Exon skipping; Muscular dystrophy; Morpholino; Exon; Biology; Dystrophin; Skeletal muscle; Molecular biology; mdx mouse; Cell biology; Extracellular matrix; Endocrinology; Biochemistry; Genetics; Gene; Zebrafish","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":[0.0004588539,0.0004138156,0.0003630243,0.0002410668,0.0002714073,0.0002802088,0.0002597244,0.0004963105,0.001160744],"category_scores_gemma":[0.0003117182,0.0002997989,0.0003037557,0.0001029306,0.0002679987,0.0001269673,0.0002157681,0.0005000453,0.0002856772],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002758116,"about_ca_system_score_gemma":0.0003315058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007723796,"about_ca_topic_score_gemma":0.001725669,"domain_scores_codex":[0.9997432,0.00006132581,0.00004546763,0.00005950969,0.00004735693,0.000043209],"domain_scores_gemma":[0.9997625,0.00008487495,0.00006752483,0.00002322938,0.00002040467,0.00004142538],"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":[0.00006119571,0.00001757867,0.00003996469,0.00002350053,0.000004345407,0.00005969129,0.000009431124,0.0001052344,0.998835,0.00009532848,0.00002455065,0.0007242384],"study_design_scores_gemma":[0.00006913386,0.0005165498,0.0009796186,0.000009188927,0.000044398,0.0003843386,0.00002018645,0.001227911,0.9947562,0.00008021289,0.001902756,0.00000948777],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9884376,0.0009305411,0.008252623,0.0001269029,0.0001221178,0.00008841177,0.0001880805,0.00014935,0.001704402],"genre_scores_gemma":[0.987609,0.0008499195,0.008713515,0.0001082079,0.00002386208,0.00007456505,0.0003294451,0.00005240601,0.00223897],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001160744,"threshold_uncertainty_score":0.003883064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03027316427913046,"score_gpt":0.411918115245168,"score_spread":0.3816449509660376,"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."}}