{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009767199,0.0002544903,0.00009876545,0.0001515347,0.0001068698,0.000330393,0.0001493548,0.0002355891,0.001140234],"category_scores_gemma":[0.0001733083,0.0001497995,0.00018551,0.0001332283,0.0001800984,0.0002526283,0.0002138865,0.0003302453,0.0007153828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002174806,"about_ca_system_score_gemma":0.0001595821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001206623,"about_ca_topic_score_gemma":0.0002810428,"domain_scores_codex":[0.9999095,0.0000154698,0.000006929627,0.00001721178,0.00003575004,0.00001514748],"domain_scores_gemma":[0.999941,0.00001592593,0.00001799953,0.000009237808,0.00000722851,0.000008572353],"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":[0.00002866838,0.00001123096,0.0001015142,0.0001486504,0.000006842153,0.00007967048,0.00003375063,0.0006855114,0.9888657,0.003186387,0.0001248619,0.006727226],"study_design_scores_gemma":[0.000006705854,0.0001239923,0.0003002858,0.00001179722,0.00000662927,0.0002553207,0.00001314616,0.0009014871,0.9793529,0.0005332365,0.01848791,0.000006609108],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8658087,0.003530461,0.09602951,0.0002993041,0.0001192471,0.0001637033,0.0005308199,0.0007284716,0.03278977],"genre_scores_gemma":[0.9246098,0.002551154,0.06190663,0.0001471998,0.00001853343,0.0001388549,0.0005749006,0.0001148527,0.009938195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001140234,"threshold_uncertainty_score":0.003814459,"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."}}