{"id":"W4362457937","doi":"10.1038/s41587-023-01679-x","title":"Combinatorial design of nanoparticles for pulmonary mRNA delivery and genome editing","year":2023,"lang":"en","type":"article","venue":"Nature Biotechnology","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":274,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"National Heart, Lung, and Blood Institute; National Institutes of Health; University of Toronto; Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology","keywords":"Genome editing; Cas9; CRISPR; Gene delivery; Computational biology; Messenger RNA; RNA; Gene; Genetic enhancement; Biology; Genetics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002606714,0.0004359178,0.0003949614,0.000325872,0.0002327525,0.0007953538,0.0004876991,0.0005764845,0.0009368343],"category_scores_gemma":[0.0002740196,0.000324157,0.0004099329,0.0002085346,0.0002373273,0.000345863,0.0004029684,0.0006507653,0.0006499286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006883882,"about_ca_system_score_gemma":0.0003371339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003731996,"about_ca_topic_score_gemma":0.001227202,"domain_scores_codex":[0.9997332,0.0000398307,0.00001793301,0.00007691873,0.00006911067,0.00006310735],"domain_scores_gemma":[0.9998847,0.00002884549,0.00002529218,0.0000128336,0.00002242142,0.00002595848],"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":[0.0001438469,0.00009544264,0.0001347838,0.0001154659,0.00002617042,0.0001316958,0.00002789599,0.003350638,0.9831216,0.003395879,0.0003957674,0.009060875],"study_design_scores_gemma":[0.0000268721,0.0001996229,0.0001820259,0.00000678467,0.00002430324,0.0001289553,0.00001560333,0.009178303,0.984917,0.0003445989,0.004961358,0.00001465629],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7448448,0.004065411,0.2275217,0.0005409773,0.0003147807,0.0005796764,0.0005892211,0.001005857,0.02053759],"genre_scores_gemma":[0.9421019,0.0009331545,0.05071418,0.0001607326,0.00001825526,0.0002998196,0.0002731516,0.0001134657,0.005385329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009368343,"threshold_uncertainty_score":0.004994631,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0109996088404077,"score_gpt":0.2427575555006395,"score_spread":0.2317579466602318,"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."}}