{"id":"W4220832236","doi":"10.1002/anse.202200010","title":"Selection of DNA Aptamers for Sensing Uric Acid in Simulated Tears","year":2022,"lang":"en","type":"article","venue":"Analysis & Sensing","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aptamer; Uric acid; Chemistry; Hyperuricemia; Hypoxanthine; Biosensor; Gout; Detection limit; Isothermal titration calorimetry; Dendrimer; Biochemistry; DNA; Xanthine; Urate oxidase; Chromatography; Molecular biology; Enzyme; 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":[0.0004362632,0.0001637334,0.0003767597,0.0005348421,0.000186362,0.00001360364,0.00007563698,0.00008838785,0.000003541534],"category_scores_gemma":[0.00009749691,0.0001748722,0.000384259,0.001787505,0.00005653154,0.000004626083,0.00008265393,0.0001237474,1.62138e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006795313,"about_ca_system_score_gemma":0.00004048311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001198021,"about_ca_topic_score_gemma":0.0003197656,"domain_scores_codex":[0.9985517,0.0001566243,0.0003965116,0.0004432473,0.0001859471,0.0002659456],"domain_scores_gemma":[0.999262,0.00003079039,0.0002489222,0.0002666989,0.0001542979,0.00003728559],"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":[0.0001066643,0.00003670664,0.001356507,0.000006026761,0.0005604873,0.000003480057,0.00004411235,0.007459432,0.9778768,0.000002135404,0.00005461439,0.012493],"study_design_scores_gemma":[0.0003211198,0.0001767755,0.0005403578,0.000007310278,0.0007795681,0.00001276066,0.0003930725,0.1133328,0.8829796,0.00005850197,0.001147815,0.0002503961],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9890832,0.00005633922,0.01053082,0.0000668166,0.00002734297,0.0001408397,0.00001296676,0.00003098363,0.0000506945],"genre_scores_gemma":[0.9884301,0.00002284127,0.01106729,0.0001357491,0.00004402352,7.007162e-7,0.0001939632,0.00002196769,0.00008332579],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1058733,"threshold_uncertainty_score":0.7131082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008115261346647508,"score_gpt":0.2707068604406652,"score_spread":0.2625915990940177,"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."}}