{"id":"W4384008721","doi":"10.1002/adma.202300665","title":"Engineered Nanomaterials to Potentiate CRISPR/Cas9 Gene Editing for Cancer Therapy","year":2023,"lang":"en","type":"review","venue":"Advanced Materials","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; McGill University Health Centre","funders":"Guangdong Provincial Pearl River Talents Program; National Key Research and Development Program of China; Youth Innovation Promotion Association of the Chinese Academy of Sciences; China Primary Health Care Foundation; National Natural Science Foundation of China","keywords":"CRISPR; Genome editing; Cas9; Genetic enhancement; Computational biology; Nanomedicine; Viral vector; Biology; Gene; Nanotechnology; Computer science; Materials science; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004043585,0.0006098186,0.001371989,0.0001294214,0.0000880962,0.00009355672,0.0003815988,0.0003686654,0.0000573581],"category_scores_gemma":[0.0002058527,0.0005544967,0.000312859,0.0001445113,0.00001599316,0.000005280586,0.0001739761,0.00005018873,0.00004613235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004656498,"about_ca_system_score_gemma":0.000118011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001059882,"about_ca_topic_score_gemma":0.000004747636,"domain_scores_codex":[0.9976078,0.00005948493,0.0007890263,0.0007626,0.000160699,0.0006203793],"domain_scores_gemma":[0.9988608,0.00003720362,0.0002583285,0.0005588972,0.0001463281,0.0001383802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003711821,0.00001066071,2.613342e-8,0.003964502,0.0002361667,0.00000444612,0.00001181056,0.0003094044,0.8392704,0.000006912414,0.0009436709,0.1552049],"study_design_scores_gemma":[0.000225804,0.00007861736,3.089252e-7,0.0008971908,0.00008969381,0.00001003416,0.000003230577,3.472292e-7,0.4531941,0.000009009106,0.5451382,0.0003534477],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.002185075,0.9812072,0.005994141,0.00001795164,0.00554526,0.00237212,0.002540478,0.0001254708,0.00001228902],"genre_scores_gemma":[0.0002094173,0.9867386,0.004323153,0.00006651475,0.003194136,0.003026716,0.001366738,0.0003091839,0.000765541],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.5441945,"threshold_uncertainty_score":0.9996907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0374894983717245,"score_gpt":0.4035128304552069,"score_spread":0.3660233320834824,"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."}}