{"id":"W4206018206","doi":"10.20944/preprints202201.0265.v1","title":"CRISPR Therapeutics for Duchenne Muscular Dystrophy","year":2022,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Muscular Dystrophy Canada; University of Alberta","funders":"University of Alberta","keywords":"CRISPR; Genome editing; Duchenne muscular dystrophy; Dystrophin; Biology; Genetics; Gene; Muscular dystrophy; Computational biology; Guide RNA; mdx mouse; Bioinformatics","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":[0.0007573752,0.0006732387,0.0008221631,0.0007251491,0.0004013416,0.001033105,0.0005584494,0.001366659,0.01025426],"category_scores_gemma":[0.0008651678,0.0003346571,0.0005871645,0.000303869,0.0005762365,0.000388601,0.0008933847,0.002138663,0.004086622],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007236593,"about_ca_system_score_gemma":0.0006408927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005434051,"about_ca_topic_score_gemma":0.0007136039,"domain_scores_codex":[0.9991902,0.0001981523,0.00005230318,0.0001303537,0.0003586426,0.00007043695],"domain_scores_gemma":[0.9997386,0.00008815336,0.00003726494,0.00003823757,0.0000425353,0.00005510312],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0005039831,0.0002896588,0.0004858214,0.003183132,0.0002132439,0.001632592,0.0003208797,0.003334275,0.5171634,0.04749597,0.08970752,0.3356695],"study_design_scores_gemma":[0.0002499173,0.0009994804,0.001339295,0.0006301916,0.0001136447,0.003488627,0.00005247266,0.003539715,0.1628074,0.01073975,0.8159612,0.00007838052],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.06187257,0.2336048,0.4796796,0.01811073,0.008281403,0.001400697,0.007930881,0.03310025,0.156019],"genre_scores_gemma":[0.4441981,0.1629508,0.245237,0.01094864,0.001384805,0.002898017,0.01002096,0.003360883,0.1190009],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01025426,"threshold_uncertainty_score":0.0343039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07264486298437298,"score_gpt":0.386594939776455,"score_spread":0.313950076792082,"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."}}