{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000371238,0.0002832572,0.0001838924,0.0002000219,0.0001725513,0.0003433666,0.0003387097,0.0004278937,0.0006121082],"category_scores_gemma":[0.0006715558,0.0001974223,0.0001899547,0.0001719589,0.0001813534,0.0001952797,0.0001742744,0.0003751281,0.000420572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003652963,"about_ca_system_score_gemma":0.0002065758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005465238,"about_ca_topic_score_gemma":0.0007231544,"domain_scores_codex":[0.9996557,0.00004462762,0.00003399315,0.0001086615,0.0001097344,0.00004728451],"domain_scores_gemma":[0.9997272,0.00006369006,0.00004738151,0.0000357966,0.00008495592,0.00004092738],"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":[0.00001433457,0.000007888096,0.00006179619,0.000006401916,0.000001116289,0.00001073787,0.000007427564,0.00002044197,0.9991799,0.0000172421,0.000008106506,0.0006647193],"study_design_scores_gemma":[0.000001757278,0.00003058253,0.000545139,6.092354e-7,0.000002124634,0.0000563282,0.000003767486,0.0004282609,0.9986304,0.00000827339,0.0002913468,0.000001392617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9708751,0.0007692352,0.02634118,0.0001588906,0.00003062818,0.00007659348,0.000160878,0.0001224751,0.001464881],"genre_scores_gemma":[0.977604,0.0004061151,0.0170826,0.0001113411,0.000009059919,0.00005150697,0.0003435316,0.00003879804,0.00435296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006121082,"threshold_uncertainty_score":0.00265044,"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."}}