{"id":"W4393006017","doi":"10.1039/d4an00250d","title":"Characterization of nanozyme kinetics for highly sensitive detection","year":2024,"lang":"en","type":"article","venue":"The Analyst","topic":"Advanced Nanomaterials in Catalysis","field":"Materials Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo","keywords":"Kinetics; Characterization (materials science); Computer science; Nanotechnology; Materials science; Physics","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":[0.0003227321,0.00008401288,0.0001635727,0.00008471109,0.00006722176,0.00005510614,0.0001229625,0.00003776717,0.00002443346],"category_scores_gemma":[0.00004469861,0.00005725834,0.00007728946,0.0003096165,0.0000746092,0.0001388486,0.00003634316,0.0000228367,0.00004911457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003823435,"about_ca_system_score_gemma":0.00001331385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001563358,"about_ca_topic_score_gemma":0.00001516115,"domain_scores_codex":[0.9992742,0.00005344685,0.0002443831,0.0001817002,0.0001263589,0.0001198896],"domain_scores_gemma":[0.9994026,0.0001271335,0.0001123645,0.0002384618,0.000102947,0.00001645668],"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":[0.0000312468,0.000008202679,0.000001081435,0.00004266181,0.00002249365,9.367826e-7,0.0001749661,0.00007204164,0.9979439,0.0003760941,0.000006720352,0.001319604],"study_design_scores_gemma":[0.00005350652,0.0000492013,0.0001255215,0.00002538481,0.0001455907,0.000004545988,0.00003331012,0.00159579,0.9959086,0.000406888,0.001584122,0.0000675854],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8608524,0.0000365791,0.1380081,0.0001505463,0.0005447543,0.0001591916,0.000146999,0.00006702631,0.00003438962],"genre_scores_gemma":[0.9986958,0.00001607729,0.0007259397,0.00002839533,0.0002137291,0.00002420433,0.00005770681,0.00001575718,0.000222415],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1378434,"threshold_uncertainty_score":0.2334927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01109437010057819,"score_gpt":0.2551170408617015,"score_spread":0.2440226707611233,"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."}}