{"id":"W2942336661","doi":"10.1021/acs.jpcc.9b02653","title":"Unified Etching and Protection of Faceted Silver Nanostructures by DNA Oligonucleotides","year":2019,"lang":"en","type":"article","venue":"The Journal of Physical Chemistry C","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Nanomaterials; Oligonucleotide; Etching (microfabrication); DNA; Materials science; Nanotechnology; Dissolution; Polymer; Adsorption; Silver nanoparticle; Nanostructure; Nanoparticle; Chemical engineering; Chemistry; Layer (electronics); Organic 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":[0.000129356,0.000309724,0.0002431967,0.0001360504,0.0001192962,0.0002423128,0.0002939047,0.0003814602,0.0006014839],"category_scores_gemma":[0.0003088126,0.0001784169,0.0002373717,0.0001117848,0.0002379021,0.0001848947,0.000302287,0.0002535047,0.0003849919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002310996,"about_ca_system_score_gemma":0.000171255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003044257,"about_ca_topic_score_gemma":0.0005389441,"domain_scores_codex":[0.9998193,0.00001879188,0.00001462785,0.00005823129,0.00004743543,0.00004157457],"domain_scores_gemma":[0.9998654,0.00003007298,0.00004057628,0.00001765705,0.00002915279,0.00001715433],"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":[0.00001740902,0.00000313553,0.00003793715,0.00002936525,0.000001859749,0.00003381683,0.00001168955,0.00009527517,0.9981498,0.00007041449,0.00001790149,0.001531363],"study_design_scores_gemma":[0.000002950474,0.00003948199,0.0001280806,0.000001948182,0.000002085932,0.00005137552,0.000004464504,0.0006678026,0.9985084,0.00002691452,0.0005638976,0.000002542685],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9427496,0.002954023,0.04985769,0.0001223543,0.000115317,0.00005289712,0.0001891273,0.0004893124,0.003469625],"genre_scores_gemma":[0.9648913,0.001004295,0.03053722,0.00007887823,0.00001780938,0.00003465924,0.0001783499,0.00005143671,0.003206138],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006014839,"threshold_uncertainty_score":0.002012134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004211349909439132,"score_gpt":0.2279471480243842,"score_spread":0.2237357981149451,"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."}}