{"id":"W4366743024","doi":"10.1002/adma.202300387","title":"Surface Ligand Engineering Ruthenium Nanozyme Superior to Horseradish Peroxidase for Enhanced Immunoassay","year":2023,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Advanced Nanomaterials in Catalysis","field":"Materials Science","cited_by":200,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Key Research and Development Program of China; Youth Innovation Promotion Association of the Chinese Academy of Sciences; Chinese Academy of Sciences; National Natural Science Foundation of China; Innovative Research Group Project of the National Natural Science Foundation of China","keywords":"Horseradish peroxidase; Ruthenium; Materials science; Immunoassay; Ligand (biochemistry); Surface modification; Nanotechnology; Chemical engineering; Combinatorial chemistry; Organic chemistry; Catalysis; Chemistry; Enzyme; Biochemistry; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00145381,0.000636414,0.001074641,0.000256299,0.0003491796,0.0003647693,0.0008306064,0.0002032767,0.0005521828],"category_scores_gemma":[0.001207656,0.0006349058,0.0001694795,0.0007730806,0.0000837484,0.0008534956,0.0003945826,0.00007127374,0.001900641],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002531371,"about_ca_system_score_gemma":0.00008994727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002115164,"about_ca_topic_score_gemma":0.000005553556,"domain_scores_codex":[0.9957628,0.00009247067,0.001060763,0.001161052,0.0005387209,0.00138416],"domain_scores_gemma":[0.9975652,0.0004396739,0.0002693167,0.001099747,0.0003241008,0.0003019524],"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":[0.0004170449,0.0000337783,0.000001822797,0.000178936,0.00002494297,0.00001182792,0.0005106661,0.009864768,0.988133,0.000207738,0.000328083,0.0002874147],"study_design_scores_gemma":[0.001107094,0.0001871262,0.00007332947,0.0001409298,0.00004466007,0.000007890516,0.0001567903,0.00003186107,0.9901398,0.0003544117,0.006951321,0.0008047799],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9830126,0.0001047529,0.007122446,0.0002474549,0.005203856,0.001666342,0.001281224,0.001324907,0.00003640575],"genre_scores_gemma":[0.9570285,0.00007444806,0.03991296,0.0001519851,0.0004193361,0.0009458194,0.0002259476,0.0002198379,0.001021155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03279052,"threshold_uncertainty_score":0.9996102,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01107601502565392,"score_gpt":0.2643082015920315,"score_spread":0.2532321865663776,"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."}}