{"id":"W4240723707","doi":"10.1002/ange.201901192","title":"In Vitro Selection of Circular DNA Aptamers for Biosensing Applications","year":2019,"lang":"en","type":"article","venue":"Angewandte Chemie","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Aptamer; DNA; Computational biology; Circular DNA; Biology; Rolling circle replication; Biosensor; Systematic evolution of ligands by exponential enrichment; Molecular biology; Genetics; Biochemistry; RNA; Gene; DNA replication; Genome","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":[0.0005748108,0.0004844537,0.0003473771,0.0002850243,0.0001475361,0.00042753,0.0003066582,0.0003958881,0.001030526],"category_scores_gemma":[0.0007137321,0.0002783275,0.0002047387,0.0003226696,0.000215642,0.0002052304,0.0003238218,0.0004783727,0.0009179955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002451497,"about_ca_system_score_gemma":0.0001818398,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002744968,"about_ca_topic_score_gemma":0.0004320856,"domain_scores_codex":[0.9994929,0.0001422936,0.00004526461,0.0001093311,0.0001421128,0.00006807692],"domain_scores_gemma":[0.9994904,0.0002041579,0.00008141156,0.00005200029,0.0001037541,0.0000682699],"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":[0.0000256279,0.00001535013,0.00004664004,0.00002045447,0.000002774732,0.00001751228,0.00001216052,0.0001705054,0.9984391,0.00006591592,0.00003033965,0.001153641],"study_design_scores_gemma":[0.000005257592,0.0001017798,0.0001178668,0.000003036854,0.000005034437,0.0000521863,0.000006856996,0.00137863,0.9966093,0.00003030418,0.001685392,0.00000440852],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8223833,0.003754644,0.1676672,0.000340977,0.0002907471,0.0005530434,0.0006216789,0.0007786996,0.003609712],"genre_scores_gemma":[0.8940544,0.001573745,0.09523268,0.0002500407,0.00004369785,0.0002733706,0.001332672,0.0001580442,0.007081321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001030526,"threshold_uncertainty_score":0.003447473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008493252352346149,"score_gpt":0.2625210294620212,"score_spread":0.2540277771096751,"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."}}