{"id":"W4416718248","doi":"10.1002/advs.202516852","title":"Aptamer Engineering: Strategies for Discovering Functional Nucleic Acids for Next‐Generation Diagnostics and Biosensing","year":2025,"lang":"en","type":"article","venue":"Advanced Science","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada; McGill University Health Centre; McGill University","funders":"Fonds de Recherche du Québec - Santé; National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Aptamer; Nucleic acid; Systematic evolution of ligands by exponential enrichment; Biosensor; Nucleic acid detection","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001316,0.001046767,0.0008712976,0.0009279785,0.0004058662,0.001366318,0.0008287525,0.001229327,0.00167118],"category_scores_gemma":[0.000790093,0.0005531658,0.0006586271,0.0006304837,0.001214976,0.00187286,0.001265565,0.001972308,0.001684698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008547837,"about_ca_system_score_gemma":0.0006344543,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003815057,"about_ca_topic_score_gemma":0.0004912807,"domain_scores_codex":[0.999355,0.0001330143,0.0000388956,0.0001424461,0.0002656907,0.00006507392],"domain_scores_gemma":[0.9998004,0.0000748341,0.00004253785,0.00002194934,0.00003926915,0.00002111312],"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":[0.0001071348,0.0001099874,0.0002977811,0.002327871,0.00008086972,0.0003859942,0.0002607748,0.002984164,0.7569411,0.04812254,0.003712462,0.1846694],"study_design_scores_gemma":[0.00004948822,0.0004763497,0.0003294095,0.0003135122,0.0000741277,0.001485426,0.0001132974,0.008926086,0.6520937,0.02409454,0.3119627,0.00008129363],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03654703,0.1884898,0.7381793,0.003595741,0.00147245,0.0005749715,0.0004311354,0.001258144,0.02945145],"genre_scores_gemma":[0.2548348,0.2708412,0.4324754,0.004483057,0.0007101091,0.001201143,0.001055006,0.0003830906,0.03401621],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00167118,"threshold_uncertainty_score":0.006959736,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01906310379480251,"score_gpt":0.2858957212531917,"score_spread":0.2668326174583892,"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."}}