{"id":"W2300872164","doi":"10.1002/cbic.201600136","title":"Nanostructures from Synthetic Genetic Polymers","year":2016,"lang":"en","type":"article","venue":"ChemBioChem","topic":"Advanced biosensing and bioanalysis techniques","field":"Biochemistry, Genetics and Molecular Biology","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"European Social Fund; Biotechnology and Biological Sciences Research Council; Directorate for Biological Sciences; Medical Research Council; European Science Foundation; University of Oxford; Cancer Research UK","keywords":"Nucleic acid; RNA; DNA; Polymer; Chemistry; Nanotechnology; Polynucleotide; Computational biology; Biochemistry; Biology; Materials science; Gene; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.00004012087,0.0002046637,0.0001591344,0.0000340446,0.00005995347,0.00001553525,0.000220991,0.0001957416,0.00004115668],"category_scores_gemma":[0.00009114847,0.0001352758,0.000139537,0.0000767032,0.0001847347,0.000002394522,0.0001024496,0.00004276661,0.00001742565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001751968,"about_ca_system_score_gemma":0.00002939016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001436644,"about_ca_topic_score_gemma":0.0000075179,"domain_scores_codex":[0.9988982,0.00002467529,0.0001820049,0.0005062566,0.0001257151,0.0002631616],"domain_scores_gemma":[0.9991885,0.00001589296,0.00008185634,0.0005648356,0.0000518007,0.00009710322],"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":[0.00003065264,0.00001593292,0.0004254646,0.000002163647,0.00005231726,0.000003029069,0.000004922028,7.402751e-8,0.9679132,0.000009771956,0.001373248,0.03016925],"study_design_scores_gemma":[0.0002403771,0.00005763318,0.0008315858,0.00002547124,0.00003213649,0.000008762698,0.00001570272,0.000001214345,0.9805735,0.0003543586,0.01760625,0.0002529678],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9954205,0.0008693651,0.00196738,0.0003507776,0.0001114964,0.00007154312,0.00005356516,0.00007232044,0.001083056],"genre_scores_gemma":[0.993068,0.000248944,0.004426942,0.0003035539,0.0003232176,0.000006952851,0.00004823278,0.00002973759,0.001544393],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02991629,"threshold_uncertainty_score":0.5516387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00474720741886701,"score_gpt":0.2257932714385436,"score_spread":0.2210460640196766,"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."}}