{"id":"W4411186707","doi":"10.3390/ph18060864","title":"Engineering Lipid–Polymer Nanoparticles for siRNA Delivery to Cancer Cells","year":2025,"lang":"en","type":"article","venue":"Pharmaceuticals","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Internalization; Nucleic acid; RNA interference; Polymer; Cationic polymerization; Chemistry; Gene silencing; Nanoparticle; Computer science; Nanotechnology; Flexibility (engineering); Drug delivery; Rational design; Small interfering RNA; Combinatorial chemistry; Computational biology; RNA; Materials science; Cell; Biochemistry; Biology; Mathematics; Organic chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.00009863934,0.0001310674,0.0001242607,0.00005170221,0.00004822686,0.00002771413,0.0001786385,0.00006991963,0.00006994406],"category_scores_gemma":[0.0000375429,0.0001290252,0.00008857867,0.0000965392,0.0000200061,0.000003841002,0.0001011532,0.00005024836,0.00004293281],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001507113,"about_ca_system_score_gemma":0.00005447453,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000111698,"about_ca_topic_score_gemma":0.000005936338,"domain_scores_codex":[0.9991621,0.0000150351,0.0001702011,0.0002881729,0.00006063417,0.0003038893],"domain_scores_gemma":[0.9995787,0.00003176389,0.00001802499,0.0001751963,0.00007944787,0.000116934],"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":[0.0001248406,0.00003454356,0.0001336057,0.0000347885,0.00008225333,6.172654e-7,0.00001671104,0.0004866259,0.9752815,0.00007113523,0.01528892,0.008444434],"study_design_scores_gemma":[0.000293866,0.00004710868,0.00005188243,0.00002567373,0.00004005276,4.210873e-7,0.00001211344,0.0007175894,0.8327674,0.00000713525,0.1659079,0.0001288522],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9918635,0.002749683,0.003094926,0.000982131,0.0006503886,0.000300084,0.00005120514,0.00002158361,0.0002864806],"genre_scores_gemma":[0.9924067,0.0004589702,0.0003909404,0.003937619,0.0002898165,0.0001979207,0.000009437037,0.0000161753,0.002292461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.150619,"threshold_uncertainty_score":0.5261495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02332235976462419,"score_gpt":0.3418705305263436,"score_spread":0.3185481707617194,"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."}}