{"id":"W3165883155","doi":"10.1021/acs.nanolett.0c05056","title":"Isolating Nanoparticles from Complex Biological Media by Immunoprecipitation","year":2021,"lang":"en","type":"article","venue":"Nano Letters","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital du Saint-Sacrement; Wilfrid Laurier University; Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies; Fonds de Recherche du Québec - Santé; Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Nanomedicine; Polyethylene glycol; Immunoprecipitation; PEG ratio; Nanotechnology; In vivo; Nanoparticle; Ex vivo; Chemistry; Biophysics; Materials science; In vitro; Biochemistry; Biology","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":[0.0004434405,0.0007711793,0.0003730235,0.0004878464,0.0002917706,0.0004672833,0.0004197273,0.0004531851,0.0008078969],"category_scores_gemma":[0.0004265584,0.0002484813,0.0003951333,0.0001729061,0.0003683018,0.0004101269,0.0004861002,0.0009943481,0.001552525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000246369,"about_ca_system_score_gemma":0.0002514262,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002412206,"about_ca_topic_score_gemma":0.0005785344,"domain_scores_codex":[0.9996358,0.00007139469,0.00003812215,0.0001104139,0.00009189265,0.00005237474],"domain_scores_gemma":[0.9997085,0.000115106,0.00004645986,0.00004292505,0.00006424926,0.0000227684],"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":[0.00002124953,0.00002043881,0.0001277303,0.00007301181,0.00000874682,0.00004641763,0.00002561287,0.00007171314,0.9954649,0.0002273523,0.0001323116,0.003780538],"study_design_scores_gemma":[0.000003399615,0.00003573633,0.0002728301,0.000004300542,0.000007329274,0.0001080005,0.000009193415,0.0007641599,0.9959115,0.00009779291,0.002779867,0.000005943356],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4362006,0.006181672,0.5454738,0.001146395,0.0004596809,0.000551826,0.0006510736,0.00158351,0.007751388],"genre_scores_gemma":[0.6896576,0.004959875,0.2906126,0.001163176,0.0002375908,0.0004943067,0.002401236,0.0005431424,0.009930499],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008078969,"threshold_uncertainty_score":0.002702713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02784742299557449,"score_gpt":0.2398151110426279,"score_spread":0.2119676880470534,"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."}}