{"id":"W3013652494","doi":"10.1116/6.0000027","title":"Human plasma protein adsorption to elastin-like polypeptide nanoparticles","year":2020,"lang":"en","type":"article","venue":"Biointerphases","topic":"Blood properties and coagulation","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; King Saud University; Alberta Innovates - Technology Futures","keywords":"Biocompatibility; Chemistry; Fibrinogen; Nanoparticle; Blood proteins; Albumin; Complement system; Biophysics; Complement factor I; Protein adsorption; Adsorption; Antithrombin; Immunoglobulin G; Fibronectin; Von Willebrand factor; Coagulation; Biochemistry; Antibody; Platelet; Nanotechnology; Materials science; Immunology; Extracellular matrix; Organic chemistry; Heparin; 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":[],"consensus_categories":[],"category_scores_codex":[0.00003765075,0.0001214207,0.0001699221,0.00004541978,0.00005509755,0.0000317018,0.00006184674,0.00003992639,0.0003413183],"category_scores_gemma":[0.00006366849,0.00009830285,0.00006880552,0.0001394905,0.0000283905,0.00007262047,0.00004746623,0.00006760239,0.0003852596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002167503,"about_ca_system_score_gemma":0.00002531739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000591678,"about_ca_topic_score_gemma":0.00001833496,"domain_scores_codex":[0.9991782,0.00002178277,0.000217731,0.000236661,0.0001620603,0.0001835805],"domain_scores_gemma":[0.9995339,0.000006373104,0.00004290038,0.0001401654,0.00004969869,0.0002269416],"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":[0.0004093524,0.0001105,0.001267558,0.00004679215,0.00002493236,0.00001110848,0.000256078,0.00000673616,0.9883131,0.0001106613,0.004078878,0.005364285],"study_design_scores_gemma":[0.001761387,0.003339667,0.007194505,0.0003664051,0.00008613538,0.00003090654,0.0002479349,0.001357889,0.961624,0.00001997925,0.02373878,0.0002324067],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9923584,0.00008554674,0.000232837,0.005983079,0.00005871035,0.0004935997,0.000006516865,0.0001652965,0.0006160024],"genre_scores_gemma":[0.9949547,8.044755e-7,0.001077932,0.002585664,0.0002661342,0.00003782317,0.00001293234,0.00002145213,0.00104253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02668911,"threshold_uncertainty_score":0.4951861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04182753680081446,"score_gpt":0.2733783978214753,"score_spread":0.2315508610206609,"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."}}