{"id":"W4400600124","doi":"10.1002/cbic.202400444","title":"<i>In Vitro</i> Selection and Characterization of a Light‐up DNA Aptamer for Thiazole Orange","year":2024,"lang":"en","type":"article","venue":"ChemBioChem","topic":"DNA and Nucleic Acid Chemistry","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Aptamer; DNA; Thiazole; Chemistry; Combinatorial chemistry; In vitro; Selection (genetic algorithm); Orange (colour); Systematic evolution of ligands by exponential enrichment; Computational biology; Biochemistry; Biology; Molecular biology; Stereochemistry; Computer science; Gene; Food science; Artificial intelligence; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000112426,0.0001513714,0.0001707886,0.0001074339,0.0001120701,0.000204443,0.0001621294,0.0002619992,0.0007073618],"category_scores_gemma":[0.0002536238,0.0001038692,0.0001481602,0.00009487607,0.0001125663,0.00007696593,0.00009361869,0.000208607,0.0004930696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001859736,"about_ca_system_score_gemma":0.00009270261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007206093,"about_ca_topic_score_gemma":0.000895663,"domain_scores_codex":[0.9998529,0.00002968675,0.000007514817,0.00003047686,0.00005158456,0.00002774498],"domain_scores_gemma":[0.9998547,0.00003723932,0.00003756215,0.00001374254,0.00003182127,0.00002494583],"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":[0.00000566787,0.000002867492,0.00005466389,0.000003745669,5.302563e-7,0.00001252881,0.000005052679,0.00004628702,0.999674,0.000007557777,0.00000612923,0.0001810061],"study_design_scores_gemma":[0.000001398764,0.0000544691,0.0008547804,6.827727e-7,0.000001932785,0.00006904701,0.000005930746,0.0005918242,0.9980029,0.000004308357,0.0004108486,0.000001816378],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9883712,0.0001670268,0.01007414,0.00005035008,0.00001086876,0.00004023856,0.000164522,0.00006762318,0.001054031],"genre_scores_gemma":[0.9868163,0.0001076344,0.009541848,0.00004031931,0.000003849216,0.00003695422,0.0003543113,0.00003053319,0.003068199],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007206093,"threshold_uncertainty_score":0.002366364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004823060667863572,"score_gpt":0.221285723851169,"score_spread":0.2164626631833055,"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."}}