{"id":"W1984698021","doi":"10.1021/acs.biomac.5b00221","title":"Tailoring the Surface of a Gene Delivery Vector with Carboxymethylated Dextran: A Systematic Analysis","year":2015,"lang":"en","type":"article","venue":"Biomacromolecules","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Polytechnique Montréal; National Research Council Canada","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Nanocarriers; Gene delivery; Chemistry; Coating; Biophysics; Nanotechnology; In vivo; Drug delivery; Materials science; Genetic enhancement; Biochemistry; Gene; Biology; Biotechnology","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":[0.0002752267,0.000188104,0.0003267408,0.00007314859,0.00004815779,0.00003106151,0.0003322308,0.00009468807,0.000004065744],"category_scores_gemma":[0.00004185343,0.0001180742,0.0001740823,0.000502172,0.0001160389,0.000004568539,0.00006314317,0.00004778365,0.000007375483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001539704,"about_ca_system_score_gemma":0.0001274993,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002935207,"about_ca_topic_score_gemma":0.0002566031,"domain_scores_codex":[0.9988037,0.0001542174,0.0002960061,0.0002964546,0.0002325638,0.000217111],"domain_scores_gemma":[0.9988973,0.00002320331,0.0001711327,0.00052813,0.0002888141,0.00009146435],"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":[0.0001553981,0.00004038309,0.001771347,0.0002151809,0.001528744,0.00001872232,0.000210365,0.0007158518,0.9952274,0.00002095559,0.00006756131,0.00002809164],"study_design_scores_gemma":[0.0004098279,0.0004804826,0.001292776,0.0001429825,0.0008270024,0.00003376513,0.0005360692,0.0003823218,0.9956052,0.000006755766,0.00006633246,0.0002165404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9908259,0.00506891,0.003557722,0.00004419099,0.00005938394,0.0002477252,0.00002808799,0.00001318546,0.0001548892],"genre_scores_gemma":[0.9985638,0.00005060415,0.001100647,0.00004002765,0.00003464112,0.00001821503,0.00005360534,0.00001872838,0.0001197387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007737888,"threshold_uncertainty_score":0.4814927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01792662802596548,"score_gpt":0.2354401029387548,"score_spread":0.2175134749127893,"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."}}