{"id":"W4405972253","doi":"10.1021/jacs.4c13768","title":"Kinetic and Affinity Profiling Rare Earth Metals Using a DNA Aptamer","year":2025,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Aptamer; Rare earth; Biomolecule; DNA; Profiling (computer programming); Nanotechnology; Combinatorial chemistry; Computational biology; Environmental chemistry; Biochemistry; Molecular biology; Mineralogy","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":[0.0002382267,0.0005372316,0.0004388288,0.0004942429,0.0001599311,0.0004121767,0.0004605177,0.0007942395,0.0006623145],"category_scores_gemma":[0.0005096486,0.0003341476,0.0003507693,0.0003309702,0.0002755803,0.0003129856,0.000229888,0.0006395951,0.0007149081],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005696252,"about_ca_system_score_gemma":0.0002678467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007632061,"about_ca_topic_score_gemma":0.001295799,"domain_scores_codex":[0.9994288,0.00004818893,0.00002988611,0.0002462383,0.0001632194,0.00008361232],"domain_scores_gemma":[0.9997174,0.00007004041,0.00006866304,0.00002269016,0.00007931231,0.00004180538],"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":[0.00003148707,0.00001394974,0.0001364868,0.00002112336,0.000002911219,0.00001037958,0.00001743726,0.0001538387,0.9976493,0.00002730609,0.00002069572,0.001915234],"study_design_scores_gemma":[0.000005121336,0.00008933161,0.0003509586,0.000001908382,0.000006181942,0.00005980044,0.000008009471,0.002646036,0.9961882,0.00002259997,0.0006134893,0.000008324259],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9226273,0.002036133,0.07111593,0.0002886769,0.00009584376,0.0001804099,0.0003841626,0.0008060458,0.002465522],"genre_scores_gemma":[0.9178208,0.0008030956,0.07284303,0.000291047,0.00002236536,0.0001798171,0.000568086,0.00006206371,0.007409687],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007942395,"threshold_uncertainty_score":0.004132926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081143813941133,"score_gpt":0.2857930234643321,"score_spread":0.2749815853249208,"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."}}