{"id":"W4390401714","doi":"10.1016/j.csbj.2023.12.036","title":"Combining Off‐flow, a Nextflow‐coded program, and whole genome sequencing reveals unintended genetic variation in CRISPR/Cas-edited iPSCs","year":2023,"lang":"en","type":"article","venue":"Computational and Structural Biotechnology Journal","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; SickKids Foundation; Hospital for Sick Children","funders":"Hospital for Sick Children; McLaughlin Centre, University of Toronto; University of Toronto; Canada Foundation for Innovation; Sick Kids Foundation; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Autism Speaks","keywords":"CRISPR; Biology; Sanger sequencing; Genetics; Genome editing; Locus (genetics); Computational biology; Genome; Induced pluripotent stem cell; Genomics; Human genome; DNA sequencing; Gene; Embryonic stem cell","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":[0.001625353,0.0007817086,0.0008656102,0.0006914493,0.0008293465,0.0009376776,0.0007491405,0.0008330116,0.007399098],"category_scores_gemma":[0.0009924212,0.0004656532,0.0008296781,0.00044309,0.0006332093,0.0005140065,0.0009155889,0.001289581,0.001518045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004687332,"about_ca_system_score_gemma":0.0008224036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002275139,"about_ca_topic_score_gemma":0.003541315,"domain_scores_codex":[0.9994863,0.00003681241,0.00003102145,0.0002106889,0.0001404303,0.00009474521],"domain_scores_gemma":[0.9992661,0.0004119466,0.00006704731,0.00009690391,0.00008741248,0.00007055862],"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":[0.0006105892,0.0001995412,0.004491134,0.0002580542,0.00008212838,0.0003038151,0.0003822389,0.002344946,0.9225687,0.001710567,0.004869629,0.06217861],"study_design_scores_gemma":[0.00008629769,0.0001712802,0.01050632,0.00003410704,0.00007322858,0.0004070201,0.00006792368,0.06435819,0.9033182,0.001548625,0.01934169,0.0000872164],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5787637,0.0003806022,0.3677557,0.0003764713,0.0003004575,0.0003550113,0.009483426,0.03163229,0.01095236],"genre_scores_gemma":[0.5432128,0.0004689608,0.4079016,0.000907874,0.0000532481,0.001345389,0.01620751,0.01431697,0.01558562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007399098,"threshold_uncertainty_score":0.0247525,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01006667110485376,"score_gpt":0.2803465845364063,"score_spread":0.2702799134315525,"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."}}