{"id":"W3033042675","doi":"10.1039/d0sc01080d","title":"Good's buffers have various affinities to gold nanoparticles regulating fluorescent and colorimetric DNA sensing","year":2020,"lang":"en","type":"article","venue":"Chemical Science","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; National Institute for Nanotechnology; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; University of Waterloo; Global Water Futures; Canada First Research Excellence Fund; Shanxi University","keywords":"Affinities; Fluorescence; Binding affinities; Colloidal gold; Chemistry; Nanotechnology; Nanoparticle; Adsorption; Combinatorial chemistry; DNA; Chromatography; Materials science; Biochemistry; Organic chemistry; Receptor","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":[0.0001689176,0.0001255591,0.0001354954,0.00004510564,0.000114438,0.00007316894,0.0001664244,0.00006581174,4.727817e-7],"category_scores_gemma":[0.0006022335,0.000108055,0.00003742176,0.000506765,0.0004300997,0.000007724321,0.0002982178,0.00006797892,0.000001507074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002852075,"about_ca_system_score_gemma":0.00004162657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001094739,"about_ca_topic_score_gemma":0.000002729898,"domain_scores_codex":[0.9988207,0.00001489825,0.0001564696,0.0004933128,0.0002100653,0.0003045108],"domain_scores_gemma":[0.999412,0.00002015645,0.00004978836,0.0001636517,0.00009018143,0.0002642161],"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":[0.00002298915,0.000008919085,0.000225609,0.000005419218,0.000004539365,0.000002109083,0.0000683809,0.000004259692,0.9916997,0.00002540205,0.0002016253,0.00773105],"study_design_scores_gemma":[0.00008929115,0.0001149366,0.0001659264,0.00001288278,0.00001164701,0.000009432084,0.0001260532,0.0008054887,0.9975259,0.00004107218,0.0009319977,0.0001653451],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980652,0.00008250158,0.0005827968,0.0007577816,0.00002042568,0.00008992745,0.000003104181,0.00004651814,0.000351793],"genre_scores_gemma":[0.9801449,0.00001719251,0.01878793,0.0009116342,0.0001006531,0.000001067175,0.000003978846,0.000008058436,0.00002456343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01820513,"threshold_uncertainty_score":0.4406354,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01536511749789243,"score_gpt":0.2574989307785913,"score_spread":0.2421338132806988,"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."}}