{"id":"W2528752965","doi":"10.1021/jacs.6b08369","title":"Optimized DNA “Nanosuitcases” for Encapsulation and Conditional Release of siRNA","year":2016,"lang":"en","type":"article","venue":"Journal of the American Chemical Society","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":237,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"DOD Prostate Cancer Research Program; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; McGill University; Fonds Québécois de la Recherche sur la Nature et les Technologies; Prostate Cancer Canada; Canada Research Chairs; Government of Canada","keywords":"Chemistry; Förster resonance energy transfer; Nuclease; DNA; Oligonucleotide; Computational biology; Biophysics; DNA nanotechnology; Drug delivery; Nucleic acid; In vitro; Cell biology; Nanotechnology; Fluorescence; Biochemistry; 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":[0.0001342425,0.00006862639,0.000174033,0.000007702773,0.00003227088,0.000003612288,0.00009727658,0.0000446854,8.602856e-7],"category_scores_gemma":[0.0002193364,0.00003545938,0.0003377995,0.00005707106,0.0003811284,0.000004054543,0.00004326743,0.00004239883,2.775377e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001813477,"about_ca_system_score_gemma":0.00003349464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001185218,"about_ca_topic_score_gemma":8.074594e-8,"domain_scores_codex":[0.9994676,0.00002235022,0.0002245541,0.00009312845,0.0001098432,0.00008257311],"domain_scores_gemma":[0.999088,0.0000586133,0.0005361495,0.0001048887,0.0001722634,0.00004010908],"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":[0.0001478928,0.00002704849,0.0001866352,0.000004072291,0.00007709482,1.089787e-7,0.000004916358,0.000002957885,0.9941288,0.00001017993,0.002702239,0.002708025],"study_design_scores_gemma":[0.0004971655,0.0001420225,0.000351553,0.00002166229,0.00005660066,0.00002574429,0.00002555268,0.00003639354,0.9970119,0.0005533824,0.001219126,0.00005887656],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833295,0.00006015709,0.01537138,0.001133707,0.00001513637,0.00004841422,0.00003261617,0.000002502419,0.00000657997],"genre_scores_gemma":[0.9709045,0.0002192193,0.02840752,0.0002848585,0.0001332814,0.00000113366,0.00000489513,0.000005950406,0.0000386519],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01303613,"threshold_uncertainty_score":0.1445991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007383351949147894,"score_gpt":0.2678468381829097,"score_spread":0.2604634862337618,"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."}}