{"id":"W4320921326","doi":"10.1016/j.ymthe.2023.02.009","title":"A luciferase reporter mouse model to optimize in vivo gene editing validated by lipid nanoparticle delivery of adenine base editors","year":2023,"lang":"en","type":"article","venue":"Molecular Therapy","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia Hospital; FPInnovations; University of British Columbia","funders":"Genome British Columbia; Michael Smith Health Research BC","keywords":"Luciferase; Bioluminescence imaging; Bioluminescence; Reporter gene; CRISPR; In vivo; Genome editing; Gene; Gene delivery; Genome; Molecular biology; Chemistry; Computational biology; Biology; Genetic enhancement; Biochemistry; Genetics; Gene expression; Transfection","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":[0.0002464067,0.0001909549,0.0002044,0.0001103967,0.00002809004,0.00001637025,0.0001693387,0.0001175697,0.00001896483],"category_scores_gemma":[0.00005228545,0.0002015205,0.0000972212,0.0002914862,0.00002266452,0.000004874503,0.00008759283,0.00006585961,0.000004648661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001369581,"about_ca_system_score_gemma":0.00003709093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002902107,"about_ca_topic_score_gemma":0.000004126193,"domain_scores_codex":[0.9986566,0.00004274358,0.0003638949,0.0003970981,0.0001979887,0.0003416536],"domain_scores_gemma":[0.999288,0.000007900931,0.00006375841,0.000436035,0.00007783696,0.0001265158],"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":[0.00009859048,0.00005969561,0.0001304621,0.000007486347,0.000034963,0.0000255227,0.00008956298,0.1437983,0.8474881,5.729593e-7,0.008036301,0.0002304319],"study_design_scores_gemma":[0.0009258046,0.0001615071,0.0000195232,0.00001118632,0.000006899262,0.000004377689,0.00003566243,0.02151058,0.9753258,0.000003949612,0.001788505,0.0002062647],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774256,0.0002764165,0.02149761,0.0001849305,0.0002410841,0.0002504238,0.00006173682,0.00003985425,0.00002236096],"genre_scores_gemma":[0.995324,0.0001737624,0.003231406,0.0003127244,0.0003445987,0.00006801687,0.0001153722,0.00005984451,0.0003703311],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1278376,"threshold_uncertainty_score":0.8217767,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01069780590812608,"score_gpt":0.2722018175366011,"score_spread":0.261504011628475,"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."}}