{"id":"W4404071968","doi":"10.1039/d4cc05410e","title":"A high affinity and selective DNA aptamer for copper ions","year":2024,"lang":"en","type":"article","venue":"Chemical Communications","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Aptamer; Copper; DNA; Chemistry; Ion; Combinatorial chemistry; Nanotechnology; Materials science; Biochemistry; Biology; Molecular biology; Organic chemistry","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":[0.0003912568,0.0006109759,0.0006501959,0.0005853217,0.0003434732,0.0002896666,0.0005455407,0.000609895,0.001226067],"category_scores_gemma":[0.0005726066,0.0003716722,0.0003344157,0.0003008234,0.000302037,0.000183035,0.0004096914,0.0005846881,0.0007735795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005088106,"about_ca_system_score_gemma":0.0003812478,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006272385,"about_ca_topic_score_gemma":0.001142922,"domain_scores_codex":[0.9994537,0.00006759945,0.00003355094,0.0001673535,0.0001579446,0.0001197337],"domain_scores_gemma":[0.9997427,0.00006423174,0.00002462619,0.00002457451,0.00007668654,0.00006722921],"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":[0.00002577787,0.00001619269,0.00008443947,0.00002131565,0.000003260358,0.00005304465,0.00001704873,0.0000807786,0.9971328,0.00005600244,0.00006561795,0.002443745],"study_design_scores_gemma":[0.00001135029,0.00008723974,0.0006710554,0.000002146305,0.000007046247,0.0002494021,0.000006665263,0.0008631613,0.9963151,0.00002547154,0.00175474,0.000006767017],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8844981,0.001317645,0.1066694,0.0005751471,0.0001854334,0.0003072281,0.00065276,0.0009388487,0.004855441],"genre_scores_gemma":[0.9317047,0.0003600562,0.05569039,0.0003165222,0.00004290501,0.000176939,0.001015206,0.00009383763,0.01059937],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001226067,"threshold_uncertainty_score":0.004101634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0199131657831522,"score_gpt":0.315847322765964,"score_spread":0.2959341569828118,"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."}}