{"id":"W4413980850","doi":"10.1073/pnas.2426094122","title":"A general genome editing strategy using CRISPR lipid nanoparticle spherical nucleic acids","year":2025,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"CRISPR and Genetic Engineering","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology","funders":"Air Force Office of Scientific Research; Division of Materials Research; Division of Electrical, Communications and Cyber Systems; Northwestern University; International Institute for Nanotechnology, Northwestern University; Air Force Research Laboratory; National Science Foundation","keywords":"CRISPR; Genome editing; Nucleic acid; Computational biology; Gene delivery; Guide RNA; Genome; DNA; Transfection; Genome engineering; Chemistry; Biology; Gene; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001534501,0.0005954555,0.0003341951,0.000193372,0.0002354663,0.0003408618,0.0004115893,0.0006140741,0.0009471641],"category_scores_gemma":[0.0001378599,0.0002454642,0.0004155781,0.0001466437,0.0003236833,0.0002868434,0.0004159733,0.0006431901,0.0008301115],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004326208,"about_ca_system_score_gemma":0.0004630611,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007023548,"about_ca_topic_score_gemma":0.001322845,"domain_scores_codex":[0.9998127,0.00001785529,0.00001452347,0.0000666939,0.00006484211,0.00002345261],"domain_scores_gemma":[0.9999332,0.000009486748,0.00001914625,0.0000150242,0.00001173259,0.00001142275],"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":[0.00001202233,0.000009512468,0.00002137533,0.00002878624,0.000003428881,0.00003753646,0.000007852342,0.0001522037,0.9971336,0.0002867583,0.00007362476,0.002233275],"study_design_scores_gemma":[0.00000465249,0.00005715556,0.00009260971,0.000001686324,0.000004313298,0.0001291388,0.000003583749,0.0009621634,0.9953869,0.00005408625,0.003298617,0.000005113782],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6001451,0.00226529,0.372515,0.0007922545,0.0003017262,0.0008504559,0.001020127,0.002993589,0.01911649],"genre_scores_gemma":[0.8545148,0.001526849,0.1268719,0.0002947599,0.00001891597,0.0003337781,0.0006548443,0.0001654826,0.01561856],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009471641,"threshold_uncertainty_score":0.003168643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02379771359160504,"score_gpt":0.3340006680754598,"score_spread":0.3102029544838547,"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."}}