{"id":"W4323649788","doi":"10.1039/d2bm02014a","title":"Optimization of precision nanofiber micelleplexes for DNA delivery","year":2023,"lang":"en","type":"article","venue":"Biomaterials Science","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; University of Victoria","funders":"British Columbia Knowledge Development Fund; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Engineering and Physical Sciences Research Council; Canada Foundation for Innovation; University of Victoria","keywords":"Nanofiber; Transfection; Nucleic acid; Nanotechnology; Polymer; Gene delivery; Chemistry; Methacrylate; DNA; Biophysics; Materials science; Biochemistry; Monomer; Organic chemistry; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001189025,0.0006180439,0.0002466657,0.0002637903,0.0001705288,0.0004685205,0.0002060768,0.0004005244,0.001292332],"category_scores_gemma":[0.001115475,0.0002052277,0.0001597074,0.0002410983,0.0002599273,0.0004491705,0.000188999,0.0003282799,0.0003075114],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005486183,"about_ca_system_score_gemma":0.0004143461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003151318,"about_ca_topic_score_gemma":0.0009833473,"domain_scores_codex":[0.9995906,0.00008517705,0.0000612559,0.0001114804,0.0001105641,0.00004099229],"domain_scores_gemma":[0.9995319,0.0001830559,0.0001281858,0.00003304121,0.00007849859,0.00004534804],"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":[0.00006074876,0.00005055411,0.00007341864,0.000033156,0.000005445569,0.00001414039,0.00002481906,0.0008852617,0.9973716,0.0001472114,0.00002750839,0.001306142],"study_design_scores_gemma":[0.00002157934,0.0001545907,0.0002773466,0.000006013387,0.000005720502,0.00001894881,0.000008742795,0.001390871,0.997207,0.00003299991,0.0008698485,0.000006239726],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9812799,0.0006547491,0.01595406,0.00007082061,0.00002901056,0.0003990379,0.0002008312,0.0001055258,0.001306131],"genre_scores_gemma":[0.9706154,0.0008571513,0.02509629,0.00004707162,0.000008822575,0.0004055847,0.0003578571,0.00007082371,0.00254103],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001292332,"threshold_uncertainty_score":0.00628823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01951790603763407,"score_gpt":0.2783781587780134,"score_spread":0.2588602527403793,"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."}}