{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001155371,0.0001420212,0.0001009282,0.00005822255,0.0001249725,0.00003506472,0.00006402657,0.0001446923,0.00005585682],"category_scores_gemma":[0.0001485904,0.0001348213,0.00007321338,0.00004803255,0.00005823572,0.00002383614,0.00004969544,0.00005598028,0.000005925414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004727398,"about_ca_system_score_gemma":0.00002451523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001526129,"about_ca_topic_score_gemma":0.00003162741,"domain_scores_codex":[0.99913,0.00001578917,0.0001838893,0.0003548242,0.0001779185,0.0001375764],"domain_scores_gemma":[0.999203,0.00001939564,0.0001047279,0.0001160302,0.0005067025,0.00005019951],"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":[0.0002765611,0.00004227065,0.0001696038,0.000009301682,0.0001550541,7.821805e-7,0.0000204496,2.387079e-7,0.9920235,0.0000483122,0.006291112,0.000962793],"study_design_scores_gemma":[0.0006378362,0.0002062415,0.001573039,0.00001726027,0.00005275321,0.00002347291,0.00006067248,0.00004574289,0.977998,0.00161123,0.01760739,0.0001663524],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9955302,0.00001164473,0.002433439,0.000477619,0.00049809,0.0001738672,0.00009216445,0.00006057429,0.0007223359],"genre_scores_gemma":[0.9883847,0.00009457608,0.005932197,0.0005624194,0.002078431,0.00002528658,0.002719475,0.00001505443,0.0001878691],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01402552,"threshold_uncertainty_score":0.5497851,"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."}}