{"id":"W568860201","doi":"10.1038/ncomms8065","title":"Sequential growth of long DNA strands with user-defined patterns for nanostructures and scaffolds","year":2015,"lang":"en","type":"article","venue":"Nature Communications","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Canadian Institutes of Health Research; Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"DNA; DNA origami; DNA nanotechnology; Sequence (biology); DNA sequencing; Nanotechnology; Nanostructure; Computer science; Computational biology; Materials science; Biology; Genetics","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":[0.000100944,0.0001014829,0.0001249611,0.0000418904,0.00007780887,0.00001449634,0.0002815604,0.0002164546,1.908887e-7],"category_scores_gemma":[0.00006250678,0.00007773851,0.00004761859,0.00008290364,0.0001513615,0.000004804434,0.0001240153,0.00009015086,3.29318e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007076927,"about_ca_system_score_gemma":0.00004570601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001574939,"about_ca_topic_score_gemma":0.0006905642,"domain_scores_codex":[0.9994997,0.00003964953,0.0001274866,0.0001573785,0.00008025586,0.00009555348],"domain_scores_gemma":[0.9988902,0.0000207695,0.00009445666,0.000635571,0.0003096944,0.0000492584],"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":[0.0004309636,0.0001647156,0.07740682,0.00006714134,0.0003679775,0.000001240997,0.0001111187,0.000003822818,0.9117166,0.004069792,0.002714673,0.002945136],"study_design_scores_gemma":[0.0007807255,0.0003992701,0.008928902,0.00003413634,0.0001230942,0.00002549343,0.00007878365,0.00003343594,0.9847831,0.0003380571,0.00427503,0.0001999709],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9928281,0.00156937,0.00427139,0.0007503784,0.00002754111,0.0002123952,0.0001446507,0.00002740072,0.0001688045],"genre_scores_gemma":[0.9722643,0.0002830996,0.0267564,0.0001048817,0.00003655965,0.00001085276,0.000487133,0.00001243294,0.00004433344],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07306651,"threshold_uncertainty_score":0.3170085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01713175412852394,"score_gpt":0.3026578013654769,"score_spread":0.285526047236953,"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."}}