{"id":"W2963820127","doi":"10.1021/acs.analchem.9b02789","title":"The Arsenic-Binding Aptamer Cannot Bind Arsenic: Critical Evaluation of Aptamer Selection and Binding","year":2019,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Canada First Research Excellence Fund; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Aptamer; Chemistry; Isothermal titration calorimetry; Dissociation constant; Arsenic; Systematic evolution of ligands by exponential enrichment; Binding constant; Binding site; Biosensor; Binding affinities; DNA; Molecular binding; Nanotechnology; Combinatorial chemistry; Biophysics; Biochemistry; Molecule; Molecular biology; Organic chemistry; RNA; Gene","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":[0.0007140676,0.0001760331,0.0002094716,0.00003243427,0.0001336292,0.00004099548,0.0001201132,0.0002266677,0.00002203805],"category_scores_gemma":[0.0005913386,0.0001337594,0.000130405,0.0002048122,0.0002509869,0.000007795909,0.00008773069,0.0001879748,0.000005477675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004434069,"about_ca_system_score_gemma":0.00009082338,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009852122,"about_ca_topic_score_gemma":0.00001025047,"domain_scores_codex":[0.9985307,0.00006567509,0.0003105919,0.0004267534,0.0003812147,0.0002850894],"domain_scores_gemma":[0.9990789,0.00008777764,0.0001127897,0.0003121017,0.0003183555,0.00009003547],"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":[0.00004274125,0.00002755903,0.002886841,0.00002566985,0.000101887,5.033696e-7,0.0000054288,0.00001037569,0.9938079,0.00007880102,0.0002379954,0.002774325],"study_design_scores_gemma":[0.000279611,0.00007234164,0.000278138,0.00003450042,0.0002639716,0.00002868329,0.0001778917,0.01006495,0.986154,0.000129581,0.002301445,0.000214878],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971991,0.0001925793,0.0001532693,0.000261126,0.00003838824,0.0001103375,0.00001074073,0.00001771413,0.002016703],"genre_scores_gemma":[0.9982035,0.0001152592,0.0004175082,0.00003595929,0.0001178126,0.000005810495,0.00004902399,0.00001723826,0.00103793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01005457,"threshold_uncertainty_score":0.5454552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01603553063478536,"score_gpt":0.3191648376966111,"score_spread":0.3031293070618257,"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."}}