{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003394919,0.0004372499,0.0003446319,0.0001242579,0.0001210586,0.000267691,0.0002938215,0.0005999511,0.00001771195],"category_scores_gemma":[0.0002889069,0.0005385062,0.0001788365,0.0001856024,0.00004411069,0.00001457662,0.0004966887,0.0004514146,0.000005135505],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001125047,"about_ca_system_score_gemma":0.0004076209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003596916,"about_ca_topic_score_gemma":0.000004736786,"domain_scores_codex":[0.9978499,0.000104286,0.000470744,0.0009163155,0.0002495996,0.0004091546],"domain_scores_gemma":[0.9982079,0.00001296935,0.0002753037,0.0009114479,0.0004385165,0.0001538483],"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":[0.00001671495,0.00003852965,0.0005827246,0.0001680981,0.0001291232,0.00002686689,0.00001630999,0.004461263,0.9944652,0.00001560178,0.00007293183,0.000006621821],"study_design_scores_gemma":[0.0002539803,0.00004187258,0.00937997,0.0003438351,0.0001228386,1.813095e-7,0.00001420602,0.01711218,0.9713396,4.362235e-7,0.0007660179,0.0006249292],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6809261,0.001669652,0.3151697,0.00004490642,0.001759728,0.0003021877,0.00004118084,0.00007887975,0.000007608351],"genre_scores_gemma":[0.975666,0.0001622567,0.02227929,0.0001239357,0.001594556,0.00004926911,0.000006320767,0.0001152051,0.00000319173],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2947398,"threshold_uncertainty_score":0.9997066,"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."}}