{"id":"W2610507924","doi":"10.1021/jacs.7b02917","title":"Development of DNA Nanostructures for High-Affinity Binding to Human Serum Albumin","year":2017,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":168,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation","keywords":"Chemistry; Human serum albumin; Amphiphile; DNA; Nucleic acid; Oligonucleotide; Biophysics; Bovine serum albumin; Plasma protein binding; Serum albumin; Drug delivery; Ligand (biochemistry); Nanoparticle; Biochemistry; Nanotechnology; Receptor; 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":[0.0001714978,0.00009726851,0.0002137596,0.000008568019,0.0002126125,0.00002340091,0.0006848414,0.00005314001,0.000003862137],"category_scores_gemma":[0.0001342234,0.00006575498,0.0002941101,0.00003026552,0.000177486,0.000004450413,0.0002512361,0.0000954358,4.749461e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002833436,"about_ca_system_score_gemma":0.00008897641,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001029021,"about_ca_topic_score_gemma":0.000005443552,"domain_scores_codex":[0.9993013,0.00001156299,0.0002819188,0.0001166886,0.0001362166,0.0001523507],"domain_scores_gemma":[0.9987899,0.00001114445,0.0007241548,0.0002739558,0.0001361749,0.00006467627],"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":[0.00005856175,0.00002349298,0.001458014,0.00000925306,0.0001189187,1.283331e-7,0.0001465957,0.000002495659,0.9895701,0.000003758512,0.006390499,0.002218194],"study_design_scores_gemma":[0.0002415515,0.0001429855,0.01318675,0.00002781344,0.00002137683,0.000004769467,0.0002018831,7.790591e-7,0.9835901,0.00005263493,0.002442247,0.00008707809],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991609,0.00001624287,0.000155985,0.0004316325,0.0001306336,0.00006583185,0.00001587591,0.000001082677,0.00002182713],"genre_scores_gemma":[0.9881797,0.000009751207,0.01110646,0.0003770515,0.0002273004,0.000002343722,0.00000281595,0.000009093734,0.00008549195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01172874,"threshold_uncertainty_score":0.268141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01783842104130098,"score_gpt":0.2920697983409087,"score_spread":0.2742313772996077,"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."}}