{"id":"W4392058550","doi":"10.1002/adsr.202300167","title":"Light‐Up Sensing Citrate Using a Capture‐Selected DNA Aptamer","year":2024,"lang":"en","type":"article","venue":"Advanced Sensor Research","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council; University of Waterloo; China Sponsorship Council","keywords":"Aptamer; DNA; Chemistry; Computational biology; Computer science; Molecular biology; Biology; Biochemistry","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":[0.0002312922,0.0005164967,0.000318897,0.0003731416,0.0001608622,0.0003195985,0.0003761078,0.0006516429,0.0007991049],"category_scores_gemma":[0.0003505723,0.0002351311,0.0002520398,0.0002052342,0.000233939,0.0001937251,0.0002676017,0.0003777757,0.0005696304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004003102,"about_ca_system_score_gemma":0.0001936355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004605995,"about_ca_topic_score_gemma":0.0005716716,"domain_scores_codex":[0.9995942,0.00006527748,0.00001792064,0.0001519692,0.0001173443,0.00005333344],"domain_scores_gemma":[0.9997658,0.00005912737,0.0000534762,0.00001769205,0.00006380037,0.00004010078],"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":[0.00001897709,0.00000917478,0.00007077611,0.00001331782,0.000002174804,0.00001333085,0.00000996349,0.00006306122,0.9987366,0.00002045001,0.00002230693,0.001019993],"study_design_scores_gemma":[0.000006010689,0.0001033826,0.0003640373,0.000001612543,0.000004796922,0.00007262958,0.000005185631,0.001294842,0.9976565,0.00001118844,0.0004742533,0.000005563376],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9380856,0.001165572,0.0572382,0.0002693691,0.00007830518,0.0001425223,0.0002711708,0.0004967737,0.002252535],"genre_scores_gemma":[0.949057,0.0003826556,0.04450716,0.000271219,0.00002164409,0.0001162578,0.000406679,0.00004019479,0.005197207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007991049,"threshold_uncertainty_score":0.002904415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04143218138324663,"score_gpt":0.3823639486515067,"score_spread":0.3409317672682601,"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."}}