{"id":"W3049383037","doi":"10.1155/2020/2907623","title":"The Development and Application of a Base Editor in Biomedicine","year":2020,"lang":"en","type":"review","venue":"BioMed Research International","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Key Research and Development Program of China; School of Medicine, New York University; York University","keywords":"CRISPR; Point mutation; Computational biology; Flexibility (engineering); Genome editing; Computer science; Biomedicine; Base (topology); Cas9; Mutation; Biology; Bioinformatics; Gene; Genetics; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001102092,0.0008019678,0.001051633,0.002210136,0.0004040171,0.001295643,0.000975021,0.001474818,0.003181478],"category_scores_gemma":[0.001158268,0.0004811981,0.0005543348,0.001619191,0.0008522674,0.002070949,0.0008750015,0.002645515,0.002544545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004857896,"about_ca_system_score_gemma":0.0008295457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004576369,"about_ca_topic_score_gemma":0.0005523018,"domain_scores_codex":[0.9995276,0.00008300958,0.00006819618,0.0001001138,0.0001869842,0.00003426517],"domain_scores_gemma":[0.9993592,0.0003553739,0.00008359566,0.00002939217,0.0001221223,0.00005035983],"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":[0.00006970666,0.00006045164,0.0001449558,0.01369223,0.00009586103,0.000464755,0.00009227528,0.0005375396,0.01789621,0.01622115,0.02203641,0.9286883],"study_design_scores_gemma":[0.00001266838,0.00008812913,0.0001960698,0.0008459126,0.00006777787,0.001755221,0.00002615568,0.0001898804,0.007961545,0.002854265,0.9859686,0.0000337465],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003966075,0.9895207,0.004873866,0.0005148099,0.0009623356,0.00001932573,0.00004760757,0.00007635993,0.003588406],"genre_scores_gemma":[0.003094727,0.9893777,0.003580627,0.0006149157,0.0004393974,0.00002375749,0.00009484655,0.00001951331,0.002754573],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.003181478,"threshold_uncertainty_score":0.01064312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04343680734732257,"score_gpt":0.4523424579262301,"score_spread":0.4089056505789075,"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."}}