{"id":"W3047477123","doi":"10.1016/j.jcyt.2020.06.008","title":"High-throughput assessment of mutations generated by genome editing in induced pluripotent stem cells by high-resolution melting analysis","year":2020,"lang":"en","type":"article","venue":"Cytotherapy","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Canadian Institutes of Health Research","keywords":"High Resolution Melt; Induced pluripotent stem cell; High resolution; Genome editing; Biology; Genome; Throughput; Embryonic stem cell; Computational biology; Genetics; Gene; Computer science; Geography; Polymerase chain reaction; Operating system","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":[],"consensus_categories":[],"category_scores_codex":[0.0001137279,0.0001558748,0.0002528355,0.00006571119,0.00004483047,0.0000185327,0.0001230451,0.0001146121,0.00002582506],"category_scores_gemma":[0.000005530298,0.0001676442,0.00008795264,0.0004114812,0.00002003352,0.000004634162,0.00003075496,0.0000958101,9.505034e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003735914,"about_ca_system_score_gemma":0.00003560443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000168781,"about_ca_topic_score_gemma":0.000029521,"domain_scores_codex":[0.9988808,0.0000608359,0.0003634277,0.0003420271,0.0001416941,0.0002111987],"domain_scores_gemma":[0.9995551,0.00001023122,0.0001302083,0.0001736902,0.0000580949,0.00007265033],"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":[0.000009497611,0.00003934253,0.0006375919,0.00001255422,0.0002147011,8.92896e-7,0.0001275794,0.09162161,0.9065228,0.000007432733,0.0002048808,0.000601167],"study_design_scores_gemma":[0.0007753581,0.0001759793,0.00182569,0.000005163475,0.00006647815,3.044276e-7,0.0001889829,0.01842349,0.9775953,0.000002324714,0.0007606973,0.0001802097],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8447327,0.0007278125,0.1540085,0.0001939304,0.00006890173,0.0001414394,0.0001017595,0.00001396477,0.00001095265],"genre_scores_gemma":[0.9954416,0.0001881406,0.003460364,0.0001723333,0.0001611343,0.00002121311,0.0005014701,0.00002614904,0.00002755558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1507089,"threshold_uncertainty_score":0.683633,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01108268486358505,"score_gpt":0.2822518430653138,"score_spread":0.2711691582017288,"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."}}