{"id":"W3163096316","doi":"10.1101/2021.05.11.443710","title":"Saturation variant interpretation using CRISPR prime editing","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lunenfeld-Tanenbaum Research Institute; Mount Sinai Hospital; Hospital for Sick Children; University of Toronto","funders":"Hospital for Sick Children; University of Pennsylvania","keywords":"CRISPR; Genome editing; Computational biology; Gene; Biology; Genome; Genetics; Computer science","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":[0.001672011,0.0009033477,0.0008203713,0.0008643846,0.0003817731,0.001348701,0.0009108915,0.0009524712,0.00405103],"category_scores_gemma":[0.002469762,0.0004594018,0.0006490211,0.000414599,0.0008370154,0.0004193388,0.001286149,0.001762814,0.001968243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005535341,"about_ca_system_score_gemma":0.0004906677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007799467,"about_ca_topic_score_gemma":0.001011831,"domain_scores_codex":[0.9986668,0.000222396,0.0001129241,0.0004673771,0.0004292589,0.0001011727],"domain_scores_gemma":[0.9980019,0.0008319818,0.0002718916,0.0005574608,0.0002423504,0.00009451918],"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":[0.0002294056,0.00003348613,0.00157063,0.0001629055,0.00005812015,0.0009089284,0.0001399097,0.00416474,0.9553806,0.00340869,0.001143729,0.03279884],"study_design_scores_gemma":[0.00001432612,0.00006943994,0.0009559094,0.00001423737,0.00002572082,0.0009664384,0.00003429314,0.01558718,0.9716721,0.001709089,0.008913837,0.00003748823],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1626599,0.0006184754,0.8180474,0.000398855,0.0002487473,0.000248715,0.001546888,0.009402682,0.006828288],"genre_scores_gemma":[0.538868,0.0005905121,0.4493486,0.0002960523,0.00004020916,0.0001726931,0.002004197,0.00200948,0.006670329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00405103,"threshold_uncertainty_score":0.01355207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00872059272146654,"score_gpt":0.2563130311908512,"score_spread":0.2475924384693847,"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."}}