{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0002797341,0.0001756059,0.0002377811,0.00003195425,0.0001741051,0.0001494594,0.0002428799,0.00007924838,0.001750075],"category_scores_gemma":[0.0003198032,0.0001629282,0.0000708244,0.0002272645,0.0001573695,0.0002636583,0.0001203391,0.00008319386,0.0009253845],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008074407,"about_ca_system_score_gemma":0.00003820636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001385554,"about_ca_topic_score_gemma":0.00001786116,"domain_scores_codex":[0.9980556,0.0003145545,0.0003950658,0.0004773514,0.0003246691,0.0004327202],"domain_scores_gemma":[0.9987306,0.0006156983,0.0001232285,0.0003450256,0.00008074034,0.0001047138],"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":[0.0000348416,0.00007181589,0.001552594,0.000002783878,0.000008587067,0.00002924081,0.0004444011,0.0000522993,0.9882201,0.00003973262,0.008596476,0.0009471455],"study_design_scores_gemma":[0.0005855768,0.00002517132,0.003805697,0.00001930707,0.00001461765,0.00000416353,0.0002250805,0.0001689613,0.9936003,0.0001343337,0.001197462,0.0002193395],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941955,0.0004052978,0.0007534077,0.003623883,0.000572724,0.00009396089,0.0001331606,0.0001731436,0.00004895775],"genre_scores_gemma":[0.9858195,0.00001026066,0.009160182,0.004645005,0.0001372217,0.00001842164,0.0001796457,0.00001926181,0.00001056639],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008406773,"threshold_uncertainty_score":0.9998525,"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."}}