{"id":"W2883430543","doi":"10.1002/anie.201806489","title":"Self‐Assembled Functional DNA Superstructures as High‐Density and Versatile Recognition Elements for Printed Paper Sensors","year":2018,"lang":"en","type":"article","venue":"Angewandte Chemie International Edition","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":70,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Canada Foundation for Innovation","keywords":"DNA; Deoxyribozyme; Physisorption; Aptamer; Biosensor; Nanotechnology; Chemistry; Nucleic acid; Self-assembly; Rolling circle replication; Combinatorial chemistry; Adsorption; Materials science; Biochemistry; Organic chemistry; Polymerase; Molecular biology; Biology","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":[0.0001427839,0.0003295329,0.0001500599,0.0001723211,0.0000794717,0.0003075313,0.0003699649,0.0004737642,0.0003909119],"category_scores_gemma":[0.0002335368,0.0002843799,0.0001755175,0.0001235825,0.0001733817,0.0002453852,0.0001948172,0.0003554791,0.000316794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003634173,"about_ca_system_score_gemma":0.0001362862,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003644226,"about_ca_topic_score_gemma":0.0008972014,"domain_scores_codex":[0.9998467,0.00002390563,0.000008828121,0.00003094988,0.00007130985,0.00001828404],"domain_scores_gemma":[0.9998665,0.00003747947,0.00003651558,0.00001083478,0.00002956634,0.00001914684],"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":[0.000005835943,0.000003202643,0.00002808563,0.00001055212,0.000001744518,0.00001638142,0.000006522073,0.00009480103,0.9991677,0.00004838427,0.00001066325,0.0006060786],"study_design_scores_gemma":[0.000002454782,0.00002696821,0.0001835299,7.254543e-7,0.000002445851,0.00003399455,0.000004896819,0.0009938,0.9982814,0.00001770199,0.0004496532,0.000002348444],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9659642,0.001500816,0.02973698,0.0001204696,0.00006628383,0.00005087982,0.0001978943,0.0002401025,0.002122382],"genre_scores_gemma":[0.9654952,0.0004986091,0.03151115,0.00006410146,0.00001224354,0.00003505379,0.0001996407,0.00002845139,0.002155519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004737642,"threshold_uncertainty_score":0.00263685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01097671824998758,"score_gpt":0.262437147253733,"score_spread":0.2514604290037454,"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."}}