{"id":"W3208363900","doi":"10.1016/j.isci.2021.103380","title":"Automated design of CRISPR prime editors for 56,000 human pathogenic variants","year":2021,"lang":"en","type":"article","venue":"iScience","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; National Institutes of Health; Sidney Kimmel Foundation; National Human Genome Research Institute; New York University; Canadian Institutes of Health Research; Defense Advanced Research Projects Agency; Melanoma Research Alliance; Brain and Behavior Research Foundation","keywords":"CRISPR; Genome editing; Computational biology; Palindrome; Cas9; Computer science; Prime (order theory); Human genome; Pipeline (software); Gene; Genome; Genetics; Biology; Programming language; 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":[0.00111017,0.0008326847,0.0009076063,0.0006124104,0.0004186355,0.001262139,0.0007861112,0.0008110165,0.004861968],"category_scores_gemma":[0.00179829,0.000771723,0.0005960964,0.00041065,0.0004030794,0.0004792824,0.0007094381,0.001549254,0.002290955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000583472,"about_ca_system_score_gemma":0.0006569952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002956525,"about_ca_topic_score_gemma":0.0009877924,"domain_scores_codex":[0.9992093,0.0001076083,0.00009675952,0.0002726094,0.0002357239,0.00007804955],"domain_scores_gemma":[0.9992248,0.0003288364,0.000145645,0.0001216536,0.00009326632,0.00008578382],"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":[0.0005604162,0.0001410912,0.001264602,0.0002517497,0.00007518678,0.0006537003,0.0001275267,0.01779078,0.9240553,0.003313838,0.001809247,0.04995659],"study_design_scores_gemma":[0.0001013184,0.000370392,0.0006486005,0.00002119192,0.0000661479,0.0004840552,0.00003247923,0.03594838,0.9357184,0.0008150128,0.02574263,0.00005134388],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3844036,0.001074237,0.5834279,0.0003764223,0.0002609825,0.001372503,0.002957723,0.01636027,0.009766413],"genre_scores_gemma":[0.4787217,0.0006468096,0.504657,0.0002595346,0.00003210414,0.0005961002,0.004469509,0.002306804,0.00831043],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004861968,"threshold_uncertainty_score":0.01626498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01405851873523578,"score_gpt":0.3165288039429584,"score_spread":0.3024702852077226,"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."}}