{"id":"W2086899725","doi":"10.3390/toxins6082435","title":"Selection and Characterization of a Novel DNA Aptamer for Label-Free Fluorescence Biosensing of Ochratoxin A","year":2014,"lang":"en","type":"article","venue":"Toxins","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":145,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; Biosensor; Ochratoxin A; Nucleic acid; Ochratoxin; DNA; SYBR Green I; Computational biology; Detection limit; SELEX Aptamer Technique; Biology; Mycotoxin; Chemistry; Molecular biology; Biotechnology; Biochemistry; Chromatography; Polymerase chain reaction; Gene; RNA","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":[0.0001269836,0.00008178305,0.0001401334,0.00004845851,0.00003238626,0.000004903775,0.00005472067,0.0000881527,2.131309e-7],"category_scores_gemma":[0.0001246943,0.00007453653,0.00003951798,0.00009732466,0.00006849602,0.000003802399,0.00003742479,0.00002412591,4.27837e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003988705,"about_ca_system_score_gemma":0.00001349469,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005416866,"about_ca_topic_score_gemma":0.00001961675,"domain_scores_codex":[0.9994844,0.00001713987,0.0001687743,0.0001778577,0.00005822974,0.00009365294],"domain_scores_gemma":[0.9995161,0.000009866125,0.0001478425,0.0001705401,0.0001327523,0.00002287902],"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":[0.00005022484,0.00005689498,0.0001574286,0.00002947012,0.00001844635,1.831857e-8,0.00001233287,3.825794e-7,0.9926068,0.0001383479,0.00001838588,0.006911238],"study_design_scores_gemma":[0.0003868738,0.0002878505,0.0007960701,0.00003128159,0.00002608686,0.000003843777,0.000006673351,0.002867801,0.9949287,0.00003954393,0.0005400783,0.00008515055],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9380732,0.00001090584,0.0616452,0.00006459752,0.00001641689,0.0001086022,0.00003760236,0.00001300271,0.00003045618],"genre_scores_gemma":[0.9643981,0.00003871626,0.0353426,0.00004952981,0.00005854746,0.000002386254,0.00005905992,0.000009810493,0.00004120046],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02632493,"threshold_uncertainty_score":0.3039511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01173500889986767,"score_gpt":0.2594944724695134,"score_spread":0.2477594635696457,"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."}}