{"id":"W2949224026","doi":"10.1021/acsanm.9b00606","title":"Entropic Trapping of DNA with a Nanofiltered Nanopore","year":2019,"lang":"en","type":"article","venue":"ACS Applied Nano Materials","topic":"Nanopore and Nanochannel Transport Studies","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; University of Ottawa","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Government of Canada","keywords":"Nanopore; Trapping; Nanotechnology; Polymer; Nanodevice; Chemical physics; DNA; Molecule; Kinetics; Nanoscopic scale; Nanoreactor; Chemistry; Gyration; Radius of gyration; Materials science; Nanoparticle; Physics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001193243,0.000306264,0.0006582394,0.0001321848,0.00004539828,0.00002172587,0.0002065635,0.0001175402,0.0003702039],"category_scores_gemma":[0.000001383896,0.0002472843,0.00004347598,0.0002445691,0.00005547005,0.00008086884,0.00002859672,0.0000492017,0.0000974736],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002438643,"about_ca_system_score_gemma":0.00002024171,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009782343,"about_ca_topic_score_gemma":0.00000493166,"domain_scores_codex":[0.9986095,0.00001007716,0.0004766502,0.0002733914,0.0002285959,0.0004018109],"domain_scores_gemma":[0.9994136,0.0000272416,0.0001080912,0.0003614036,0.00003977295,0.00004987616],"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":[0.0001004227,0.00002487929,0.0001897761,0.0004506356,0.000163371,0.000005890489,0.0003748815,0.0001270098,0.9966619,0.001480023,0.0002194677,0.0002017261],"study_design_scores_gemma":[0.001090728,0.00009052271,0.0005678283,0.000106806,0.0000503357,0.000004430856,0.0001308731,0.000001499641,0.9953427,0.0001600872,0.002143119,0.0003110895],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943733,0.0002013474,0.0001035496,0.00001752888,0.0004435342,0.0006051323,0.00006535123,0.0002338494,0.003956416],"genre_scores_gemma":[0.9989963,0.0001855218,0.0002992517,0.00002962329,0.00007979776,0.00008309544,0.00005036434,0.00006996095,0.0002061261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004622967,"threshold_uncertainty_score":0.9999979,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005369905544877669,"score_gpt":0.16667563633017,"score_spread":0.1613057307852924,"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."}}