{"id":"W4408721834","doi":"10.1016/j.ymthe.2025.03.013","title":"Try before you buy: Empirical comparison of base editing approaches","year":2025,"lang":"en","type":"article","venue":"Molecular Therapy","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre","funders":"Ögonfonden; National Eye Institute; University of Southern California; Research to Prevent Blindness; Knights Templar Eye Foundation","keywords":"Base (topology); Computer science; Computational biology; Biology; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"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":[0.06004735,0.0006167458,0.001160576,0.002596019,0.001160847,0.003426222,0.002472963,0.001884151,0.01275818],"category_scores_gemma":[0.2940241,0.0003842838,0.00108168,0.002284104,0.003263631,0.004382025,0.003131818,0.00225219,0.001755666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002051013,"about_ca_system_score_gemma":0.001484899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001735769,"about_ca_topic_score_gemma":0.002943604,"domain_scores_codex":[0.9515877,0.03277794,0.002720498,0.003092763,0.009140778,0.0006804513],"domain_scores_gemma":[0.4298362,0.5271205,0.01517688,0.01403499,0.0120489,0.00178255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.06252121,0.007087423,0.1183465,0.01127202,0.008384038,0.0003613305,0.01695815,0.004689207,0.00661247,0.03806024,0.009738815,0.7159686],"study_design_scores_gemma":[0.007966212,0.07052203,0.570623,0.00988187,0.016322,0.003504731,0.04328635,0.01995814,0.02620604,0.07976238,0.1511675,0.0007996475],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8557634,0.04478838,0.03504672,0.004270406,0.000424854,0.002095605,0.002668154,0.0002228152,0.05471971],"genre_scores_gemma":[0.9774461,0.00544643,0.00983003,0.001036948,0.00009406624,0.000778054,0.001005405,0.0001719169,0.004191029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06004735,"threshold_uncertainty_score":0.3175646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02932065386055851,"score_gpt":0.3519821885122223,"score_spread":0.3226615346516639,"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."}}