{"id":"W2605687434","doi":"10.1002/anie.201702998","title":"Poly‐cytosine DNA as a High‐Affinity Ligand for Inorganic Nanomaterials","year":2017,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":160,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education of the People's Republic of China","keywords":"Nanomaterials; DNA; Graphene; Materials science; Ligand (biochemistry); Nanotechnology; Carbon nanotube; Oxide; Cytosine; Drug delivery; Nanoparticle; Combinatorial chemistry; Chemistry; Biochemistry","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":[0.0001107471,0.0002864982,0.00007622769,0.0001592414,0.0001797957,0.0001717922,0.0002282562,0.0003412254,0.001067138],"category_scores_gemma":[0.0001207286,0.000109011,0.00008549769,0.00009610095,0.0002168314,0.0001622054,0.0001611103,0.0002835839,0.0004907893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004748617,"about_ca_system_score_gemma":0.0002210907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007561658,"about_ca_topic_score_gemma":0.001225708,"domain_scores_codex":[0.9999135,0.00001891153,0.00000338027,0.00002154469,0.00002982746,0.00001291574],"domain_scores_gemma":[0.999926,0.00002054358,0.00001043925,0.000005080483,0.00001687175,0.00002097904],"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":[0.00002230958,0.000007775071,0.00004101066,0.00002819248,0.000001879073,0.00002082271,0.00000637236,0.0001333402,0.9976553,0.0002464266,0.00008603384,0.001750501],"study_design_scores_gemma":[0.000006505198,0.00005413526,0.0001721657,0.000002432151,0.000002792371,0.00005516535,0.000003006925,0.001063779,0.9955794,0.00004418337,0.00301351,0.000002898631],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9403931,0.005379343,0.03981957,0.0006313635,0.0002190311,0.0001099516,0.0002293268,0.000447023,0.01277132],"genre_scores_gemma":[0.9681202,0.0008262629,0.02321625,0.0001326785,0.00002766947,0.00004234335,0.0001492286,0.00002387162,0.0074615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001067138,"threshold_uncertainty_score":0.003569901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334138990009082,"score_gpt":0.2941262119583989,"score_spread":0.2807848220583081,"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."}}