{"id":"W3124416426","doi":"10.1039/d0an90126a","title":"Correction: Aptamer-based strategies for recognizing adenine, adenosine, ATP and related compounds","year":2021,"lang":"en","type":"erratum","venue":"The Analyst","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; National Institute for Nanotechnology; University of Waterloo","funders":"","keywords":"Aptamer; Adenosine; Chemistry; Computational biology; Biochemistry; Biology; Genetics","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003294864,0.0003910833,0.0005187155,0.0001177991,0.0003396083,0.0001721858,0.0002524898,0.0006333374,0.000006103895],"category_scores_gemma":[0.0001272402,0.0002923229,0.000387707,0.0003560492,0.0002596594,0.000005749481,0.0001014374,0.0004825396,0.000001067946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002813197,"about_ca_system_score_gemma":0.0002564597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004797686,"about_ca_topic_score_gemma":0.0002170125,"domain_scores_codex":[0.9982939,0.0001484214,0.0004142988,0.0006710147,0.000179385,0.000292995],"domain_scores_gemma":[0.9984892,0.00007269539,0.0003731667,0.0006417676,0.0003589288,0.00006423349],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00007867373,0.00006247484,0.00002614305,0.00008207711,0.0008108739,0.00001083796,0.00003225935,0.00004807088,0.04181581,0.0000198144,0.9537249,0.003288132],"study_design_scores_gemma":[0.0005010704,0.0004030973,0.00008475672,0.0003542194,0.001597735,0.0001178961,0.0008429062,0.006847444,0.04168581,0.0002350275,0.946488,0.0008420972],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03828907,0.266738,0.2981259,0.03552756,0.1104072,0.009122231,0.003026305,0.003012012,0.2357517],"genre_scores_gemma":[0.5674316,0.005882022,0.007127828,0.001687096,0.004572746,0.0001192361,0.01860434,0.0002517597,0.3943234],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.5291425,"threshold_uncertainty_score":0.9999529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415129449073064,"score_gpt":0.2752129178614447,"score_spread":0.261061623370714,"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."}}