{"id":"W4360991491","doi":"10.1002/adma.202211420","title":"Optimizing Lipid Nanoparticles for Delivery in Primates","year":2023,"lang":"en","type":"article","venue":"Advanced Materials","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":129,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Potency; Messenger RNA; Pharmacology; Drug delivery; Drug; Nanoparticle; Ethylene glycol; RNA; Conjugated system; In vivo; Nanotechnology; Biology; Medicine; In vitro; Immunology; Virology; Materials science; Biochemistry; Chemistry; Biotechnology","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":[0.0001870412,0.0001007972,0.0001345461,0.0000477451,0.00003758979,0.00002566497,0.0001132929,0.00006278925,0.00001732114],"category_scores_gemma":[0.00008711086,0.00009831839,0.00003489631,0.00007024872,0.00002150244,0.000008984583,0.00007540884,0.00001466254,0.00004505247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001034796,"about_ca_system_score_gemma":0.00002358458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008593802,"about_ca_topic_score_gemma":0.00001625531,"domain_scores_codex":[0.9992332,0.00001985953,0.0001968379,0.000236775,0.00005473724,0.0002586069],"domain_scores_gemma":[0.9996893,0.0000173468,0.00004512362,0.000163001,0.00005763829,0.00002759795],"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":[0.0001797294,0.00001287443,0.00004121843,0.00002981518,0.000008641146,0.000001996032,0.00003876935,0.0007378251,0.9958947,0.00002644957,0.0007558705,0.002272139],"study_design_scores_gemma":[0.0004523043,0.0001516767,0.0002860909,0.00002571989,0.000004122873,0.000001416285,0.00007480608,0.00002075596,0.9915798,0.0001864602,0.007088851,0.000127986],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989321,0.0001672581,0.0001549602,0.00008799652,0.0003061588,0.0002173228,0.00004743514,0.0000329042,0.0000538456],"genre_scores_gemma":[0.9962382,0.0005346402,0.002304191,0.000188733,0.0001322804,0.0001548564,0.0001484844,0.00002036632,0.0002782332],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00633298,"threshold_uncertainty_score":0.4009307,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01579089265682958,"score_gpt":0.275568515893635,"score_spread":0.2597776232368054,"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."}}