{"id":"W4387357537","doi":"10.1002/chem.202302616","title":"Capture‐SELEX of DNA Aptamers for Sulforhodamine B and Fluorescein","year":2023,"lang":"en","type":"article","venue":"Chemistry - A European Journal","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"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","keywords":"Aptamer; Systematic evolution of ligands by exponential enrichment; Sulforhodamine B; Fluorescein; DNA; Chemistry; Computational biology; Biology; Molecular biology; Fluorescence; Physics; Optics; Biochemistry; 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":[0.0006262547,0.0008725172,0.0009153752,0.0006665991,0.0002494614,0.0007008537,0.0006062932,0.0005854808,0.001101225],"category_scores_gemma":[0.0008873338,0.0003606321,0.0005036756,0.0005266063,0.0002400397,0.0002556489,0.0006481437,0.0005118987,0.0007777647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003650923,"about_ca_system_score_gemma":0.0003282058,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004555405,"about_ca_topic_score_gemma":0.001022094,"domain_scores_codex":[0.9995582,0.00007784372,0.00003802552,0.00009278068,0.000160274,0.00007290041],"domain_scores_gemma":[0.9996281,0.0001617384,0.00005649939,0.00004036574,0.00006357409,0.00004979202],"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":[0.0001761011,0.0001559707,0.0007846343,0.0001099505,0.0000540708,0.0003396528,0.00008773025,0.002994179,0.9790436,0.0002565496,0.0002789232,0.01571875],"study_design_scores_gemma":[0.00002609089,0.0002191953,0.0007396854,0.000008367287,0.00003266719,0.0001925816,0.00004568669,0.005776474,0.9905958,0.00006790918,0.002281677,0.00001377485],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9291621,0.0008381939,0.06346264,0.0001785931,0.00006787282,0.001063338,0.001164199,0.0005848312,0.003478267],"genre_scores_gemma":[0.8948054,0.0009456332,0.07897133,0.0003241801,0.00002030245,0.0009455421,0.002544576,0.0003554359,0.02108766],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001101225,"threshold_uncertainty_score":0.003683984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01202787653679695,"score_gpt":0.2536134029184772,"score_spread":0.2415855263816802,"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."}}