{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007479565,0.0001088152,0.0001150876,0.00002906296,0.0000194019,0.0000175671,0.00006049941,0.0001543449,0.000009781621],"category_scores_gemma":[0.00001591251,0.0001083523,0.00005514357,0.00009414902,0.00002815601,0.000007259456,0.00003349639,0.00005111182,0.000001902091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001031688,"about_ca_system_score_gemma":0.00003189711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001826452,"about_ca_topic_score_gemma":7.601629e-7,"domain_scores_codex":[0.9993901,0.000005253377,0.0001464001,0.0002698133,0.00005323187,0.000135243],"domain_scores_gemma":[0.9997752,0.000005415156,0.00003593524,0.0001087517,0.00003891497,0.00003578961],"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":[0.0001044116,0.0000262451,0.00003001191,0.0002392146,0.00002324447,5.237769e-7,0.00007441514,4.630434e-8,0.9972293,0.00002621125,0.0008770676,0.001369304],"study_design_scores_gemma":[0.0003159291,0.00004221591,0.00004751267,0.00002854039,0.00001667272,0.000009788031,0.00002214755,0.0001262234,0.9595241,0.0000316737,0.03971845,0.0001167296],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980788,0.0005471702,0.0003015508,0.0003074061,0.00014756,0.0001311324,0.00003344828,0.00001537154,0.0004375489],"genre_scores_gemma":[0.9974312,0.0001218664,0.0001457039,0.0001124729,0.0002344398,0.00003862646,0.0002388175,0.00002289035,0.001654028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03884138,"threshold_uncertainty_score":0.441848,"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."}}