{"id":"W4281384029","doi":"10.1021/acs.molpharmaceut.2c00032","title":"Optimization of Lipid Nanoparticles for saRNA Expression and Cellular Activation Using a Design-of-Experiment Approach","year":2022,"lang":"en","type":"article","venue":"Molecular Pharmaceutics","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; University of British Columbia","funders":"Biotalent Canada; Engineering and Physical Sciences Research Council; British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; Michael Smith Health Research BC; Canada Foundation for Innovation; University of British Columbia; Wellcome Trust; Wellcome","keywords":"Nanoparticle; Chemistry; Biophysics; Cell biology; Computational biology; Biological system; Nanotechnology; Biology; Materials science","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":[0.0001622963,0.00009132882,0.0001055679,0.00004394722,0.00007709113,0.000006372863,0.000093186,0.00004072502,0.000008502569],"category_scores_gemma":[0.00001595259,0.00009874503,0.00004708776,0.0000664828,0.00003605017,0.000004836515,0.0001269103,0.00004109169,3.115958e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001343606,"about_ca_system_score_gemma":0.00003898496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002238328,"about_ca_topic_score_gemma":9.376193e-9,"domain_scores_codex":[0.9992934,0.00009936804,0.0001861375,0.0001869173,0.0001221171,0.0001120353],"domain_scores_gemma":[0.9996216,0.000008218482,0.000132631,0.0001343678,0.00007145606,0.00003176795],"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":[0.0001640468,0.00009148631,0.00002210836,0.00002819843,0.00002476991,2.343378e-7,0.00008904267,0.346249,0.6530919,0.000008029378,0.0000216273,0.0002095026],"study_design_scores_gemma":[0.0004964728,0.0002513681,8.240607e-7,0.000007014878,0.00002830137,0.000002468692,0.000171896,0.1664317,0.832248,0.000008580206,0.0002687736,0.00008458042],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5592197,0.0005035576,0.440001,0.000006333512,0.00002959865,0.0002194112,0.000007927487,0.000002199796,0.00001018779],"genre_scores_gemma":[0.9582922,0.00004935332,0.04143079,0.00006119488,0.00002284723,0.00004994334,0.00006673852,0.00001661382,0.00001026774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3990725,"threshold_uncertainty_score":0.4026706,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05552830917390052,"score_gpt":0.3120660815288986,"score_spread":0.2565377723549981,"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."}}