{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004170623,0.0004221438,0.0003523751,0.0000816522,0.0001388687,0.00002270458,0.0007610701,0.0003995991,0.0003486885],"category_scores_gemma":[0.00009949881,0.0004810728,0.0004801684,0.00006744661,0.00005644911,0.000001968096,0.002084427,0.0005332792,0.00003841325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005715681,"about_ca_system_score_gemma":0.0001400995,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000337352,"about_ca_topic_score_gemma":0.000006013998,"domain_scores_codex":[0.9977481,0.00007174072,0.0003998504,0.001100642,0.0002305026,0.0004491702],"domain_scores_gemma":[0.9979513,0.00001974293,0.0001521137,0.001620555,0.0001394558,0.0001168212],"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":[0.0001915292,0.0002158061,0.03244967,0.000494804,0.0008924274,0.000008832916,0.0003002847,0.0300003,0.9336473,0.0001526286,0.0004123577,0.001234001],"study_design_scores_gemma":[0.0007230037,0.0001309535,0.0228433,0.00002879413,0.000220862,0.00001036475,0.0001260948,0.0004794087,0.5226807,0.0004989902,0.451462,0.0007955327],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9664077,0.002036548,0.02754346,0.0002568465,0.001344967,0.001055548,0.0001697233,0.00007853153,0.001106658],"genre_scores_gemma":[0.9932637,0.0007222889,0.001807953,0.0002469062,0.0006746921,0.0007775385,0.0006589401,0.0001195666,0.001728411],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4510497,"threshold_uncertainty_score":0.9997641,"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."}}