{"id":"W3011033135","doi":"10.1016/j.talanta.2020.120951","title":"Selection, characterization, and electrochemical biosensing application of DNA aptamers for sepiapterin","year":2020,"lang":"en","type":"article","venue":"Talanta","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Aptamer; Chemistry; Biosensor; Detection limit; Chromatography; Systematic evolution of ligands by exponential enrichment; Dissociation constant; Biochemistry; Molecular biology; RNA; Biology; Gene","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":[],"consensus_categories":[],"category_scores_codex":[0.00003571932,0.00007436545,0.0001017553,0.00001717943,0.00003218786,0.000005899674,0.00003603317,0.00006635889,2.486327e-7],"category_scores_gemma":[0.00003323246,0.00007184926,0.00003537456,0.00008322966,0.00004567545,0.000002454369,0.00002159458,0.00002534919,2.026433e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003573804,"about_ca_system_score_gemma":0.00001000068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001104496,"about_ca_topic_score_gemma":0.000002336022,"domain_scores_codex":[0.9995328,0.000008992627,0.0001271944,0.0002057318,0.00003858778,0.00008664656],"domain_scores_gemma":[0.9997362,0.000004425417,0.00008130861,0.00006917897,0.00007140383,0.00003751035],"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":[0.00006551675,0.000008688967,0.0005110527,0.00001843089,0.00002039456,4.276796e-8,0.00001582905,6.399463e-8,0.992839,0.00002135448,0.00006114018,0.006438475],"study_design_scores_gemma":[0.0001193887,0.0001320692,0.0003649402,0.000003558044,0.0000212253,0.000007497276,0.000009034545,0.0007633538,0.9912045,0.00001935335,0.007270787,0.00008427263],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.90051,0.00001146637,0.09885676,0.0004199298,0.000005141157,0.0001319815,0.00001739209,0.00002624285,0.00002115552],"genre_scores_gemma":[0.9961162,0.00006481534,0.003022169,0.0002693517,0.0001046371,0.000005160462,0.0003786516,0.00001037817,0.00002860983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09583459,"threshold_uncertainty_score":0.2929928,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00716125728689079,"score_gpt":0.2459234239250555,"score_spread":0.2387621666381647,"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."}}