{"id":"W3023817783","doi":"10.1101/2020.05.07.083444","title":"Automated design of CRISPR prime editors for thousands of human pathogenic variants","year":2020,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; Advanced Research Projects Agency; National Institutes of Health; York University; Sidney Kimmel Foundation; Canadian Institutes of Health Research; Melanoma Research Alliance","keywords":"CRISPR; Genome editing; Computational biology; Human genome; Computer science; Human disease; Genome; Gene; dbSNP; Cas9; Prime (order theory); Genetics; Biology; Genotype; Single-nucleotide polymorphism; 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":[0.001251805,0.0009091586,0.000898821,0.0005191742,0.0003917937,0.001191921,0.0009616159,0.0007964848,0.005190644],"category_scores_gemma":[0.002061035,0.0008126489,0.0006225233,0.0003161357,0.00044189,0.0005092939,0.0008673824,0.001269115,0.002224342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005510516,"about_ca_system_score_gemma":0.0006148917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003690641,"about_ca_topic_score_gemma":0.0008535856,"domain_scores_codex":[0.9992225,0.0001160968,0.00008678778,0.0002992924,0.0002037776,0.00007149815],"domain_scores_gemma":[0.9990368,0.0004805362,0.0001562016,0.0001568948,0.00008579525,0.00008384825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001079058,0.0002251965,0.002598336,0.0004233332,0.0001539375,0.0009999555,0.0001895981,0.06329524,0.8186492,0.006677553,0.004891609,0.100817],"study_design_scores_gemma":[0.0002126568,0.0004399782,0.0007879338,0.00002521691,0.0001017134,0.0004593328,0.00004373519,0.1375169,0.8307132,0.002224528,0.02739758,0.00007734454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2468479,0.0006174777,0.7080755,0.0003179207,0.0002236694,0.0007897472,0.002159861,0.03504719,0.005920825],"genre_scores_gemma":[0.4035961,0.0003568089,0.5830649,0.0002172793,0.00003647821,0.0004453846,0.00313861,0.003022099,0.006122441],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005190644,"threshold_uncertainty_score":0.01736444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01539655937136461,"score_gpt":0.2746169704372924,"score_spread":0.2592204110659278,"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."}}