{"id":"W2269042829","doi":"10.1038/nchem.2420","title":"Transfer of molecular recognition information from DNA nanostructures to gold nanoparticles","year":2016,"lang":"en","type":"article","venue":"Nature Chemistry","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":249,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research","keywords":"Nanotechnology; DNA nanotechnology; DNA; Template; Chemistry; DNA origami; Nanoparticle; Colloidal gold; Nanostructure; DNA sequencing; Scaffold; Sequence (biology); Materials science; Computer science","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":[0.00005097154,0.0001348012,0.0001271296,0.00002334645,0.00001807629,0.000009595093,0.0001291061,0.0003965262,0.00001068509],"category_scores_gemma":[0.0001453713,0.00009512225,0.00009288709,0.0000979582,0.00005243215,0.00001290386,0.00003476039,0.00008668346,0.000003213699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001328063,"about_ca_system_score_gemma":0.00002209813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003644123,"about_ca_topic_score_gemma":0.000002093892,"domain_scores_codex":[0.9992878,0.00001367542,0.0002081147,0.0002086788,0.0001438005,0.0001379212],"domain_scores_gemma":[0.9994451,0.000009884211,0.00005240363,0.0002678197,0.000159082,0.00006564558],"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":[0.0000908782,0.00001197159,0.00003980087,0.0000127973,0.00003414498,7.864344e-7,0.000008206006,4.655263e-7,0.9698296,0.000003900459,0.0007695748,0.02919788],"study_design_scores_gemma":[0.0002373926,0.00003812469,0.0001254799,0.00005233709,0.00002703187,0.000003532527,0.00001867809,3.869725e-7,0.9914885,0.0004335912,0.007415914,0.0001590157],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974757,0.000156191,0.001349907,0.0003281101,0.00003340448,0.00007186217,0.0002442246,0.00002978584,0.0003107786],"genre_scores_gemma":[0.996164,0.00005226498,0.002844784,0.0005347966,0.00007937791,0.000005834048,0.0002646152,0.000009738601,0.00004462345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02903887,"threshold_uncertainty_score":0.3878973,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003342845786960422,"score_gpt":0.2225643856912792,"score_spread":0.2192215399043188,"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."}}