{"id":"W4288445917","doi":"10.1002/adma.202203354","title":"In Situ Characterization of the Protein Corona of Nanoparticles In Vitro and In Vivo","year":2022,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Protein Interaction Studies and Fluorescence Analysis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; Canada First Research Excellence Fund","keywords":"In situ; In vivo; Nanomedicine; Materials science; Nanoparticle; Biophysics; Particle (ecology); Protein adsorption; Nanotechnology; In vitro; Adsorption; Characterization (materials science); Biomolecule; Biological system; Chemistry; Polymer; Biochemistry; Biology; Physical chemistry; Organic chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.0001440637,0.00004302656,0.0001227315,0.00003328942,0.00001651936,0.000002138754,0.00005724198,0.00001537848,0.00002757147],"category_scores_gemma":[0.00003786879,0.00003648731,0.00001367711,0.0001021822,0.00002806346,0.000006550505,0.0001228366,0.00002136443,8.094165e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001343749,"about_ca_system_score_gemma":0.0000106006,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006085271,"about_ca_topic_score_gemma":0.00007888653,"domain_scores_codex":[0.9994797,0.00006973713,0.000217086,0.0001031002,0.00006199077,0.00006840728],"domain_scores_gemma":[0.9997684,0.000003377806,0.0001106329,0.00009475868,0.00001771134,0.000005095779],"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":[0.0003411553,0.00003872245,0.0007607677,0.00001613512,0.000003954694,5.654498e-7,0.00006276907,0.00003111049,0.9985161,0.00001239406,0.000001109491,0.0002152507],"study_design_scores_gemma":[0.0003007732,0.00003529393,0.008956663,0.0000144853,0.000001686316,6.410489e-7,0.0001122685,0.000002815033,0.9901788,0.00004635871,0.0003144276,0.00003583842],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995489,0.00006262894,0.00000521245,0.00009266415,0.00004435611,0.0001986838,0.00003451358,6.15566e-7,0.00001243306],"genre_scores_gemma":[0.9996805,0.00005860492,0.00005522075,0.00004027406,0.000006186139,0.000109936,0.000006926771,0.000003453416,0.00003885463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008337317,"threshold_uncertainty_score":0.1487909,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005035398173814692,"score_gpt":0.2325331654183951,"score_spread":0.2274977672445804,"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."}}