{"id":"W4392383065","doi":"10.1073/pnas.2307803120","title":"A magnetic separation method for isolating and characterizing the biomolecular corona of lipid nanoparticles","year":2024,"lang":"en","type":"article","venue":"Proceedings of the National Academy of Sciences","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"iCo Therapeutics (Canada); University of British Columbia","funders":"European Commission; Faculty of Medicine, University of British Columbia; British Columbia Knowledge Development Fund; National Science Foundation","keywords":"Chemistry; Biomolecule; Magnetic nanoparticles; Nucleic acid; Nanomedicine; Nanoparticle; Biophysics; Biodistribution; Nanotechnology; Iron oxide nanoparticles; Biochemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003187958,0.000620503,0.0002335445,0.000667933,0.0003700478,0.0002242609,0.0003145813,0.0005105034,0.000505928],"category_scores_gemma":[0.0003794808,0.0002124413,0.0002407204,0.0002286579,0.0003126024,0.0002727263,0.0002697614,0.0006393428,0.0005377716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000315362,"about_ca_system_score_gemma":0.0004261857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006740267,"about_ca_topic_score_gemma":0.001119403,"domain_scores_codex":[0.9997429,0.00003477991,0.00002488665,0.00007643584,0.00009338377,0.00002751475],"domain_scores_gemma":[0.9998401,0.00004120691,0.00004021414,0.00001482737,0.00004724022,0.0000164192],"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":[0.000009405975,0.000008324353,0.0000424963,0.00003343395,0.000002557596,0.0000195531,0.00001387644,0.00002462809,0.9974342,0.00008063774,0.00004057513,0.00229037],"study_design_scores_gemma":[0.000007128176,0.00007839697,0.0005749146,0.000006686901,0.00001001762,0.0002626632,0.00001006759,0.0009808078,0.9941868,0.00007012583,0.003804302,0.000008157901],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4510286,0.006557351,0.5331334,0.0008481963,0.0002772148,0.000824042,0.0005285283,0.001224726,0.005577907],"genre_scores_gemma":[0.6467491,0.003884108,0.3394134,0.0006022925,0.0001134675,0.0009627442,0.0008794524,0.0001538663,0.00724146],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006740267,"threshold_uncertainty_score":0.002288163,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03200982334292053,"score_gpt":0.3420474894709342,"score_spread":0.3100376661280136,"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."}}