{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001771655,0.0006650711,0.0005472542,0.000340239,0.0003944079,0.00034105,0.0004824407,0.000620208,0.0006575158],"category_scores_gemma":[0.002548576,0.0003598901,0.0002726785,0.0004169694,0.0004596024,0.0004123561,0.0003780264,0.0006043703,0.0002893503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004415052,"about_ca_system_score_gemma":0.0002531199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008687555,"about_ca_topic_score_gemma":0.00133786,"domain_scores_codex":[0.9978946,0.0005951984,0.0001307547,0.0003147847,0.0008795027,0.0001852323],"domain_scores_gemma":[0.9985379,0.0007638139,0.00009121212,0.0001013829,0.0004215483,0.00008416874],"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":[0.00003867188,0.000031982,0.000168631,0.00005422363,0.000006077008,0.00003406567,0.00004512375,0.0002347731,0.9954422,0.00005588047,0.00004328002,0.003845202],"study_design_scores_gemma":[0.000003541143,0.0002363213,0.0005309132,0.000003440235,0.00001415332,0.00009896545,0.00002084887,0.001531989,0.9964023,0.00003839941,0.00111073,0.000008491448],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9547358,0.005445302,0.03627706,0.0003908313,0.0001123353,0.0002835483,0.0001250226,0.0001779907,0.002452184],"genre_scores_gemma":[0.9589688,0.003595673,0.03425539,0.0002769799,0.00005247343,0.0001361078,0.0002768877,0.00007901089,0.002358696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001771655,"threshold_uncertainty_score":0.009369552,"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."}}