{"id":"W2905954642","doi":"10.1039/c8nr06442c","title":"Tuning optimum transfection of gemini surfactant–phospholipid–DNA nanoparticles by validated theoretical modeling","year":2018,"lang":"en","type":"article","venue":"Nanoscale","topic":"RNA Interference and Gene Delivery","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Regional Municipality of Waterloo; Fields Institute for Research in Mathematical Sciences; Emmanuel Bible College; University of Waterloo","funders":"Canadian Institutes of Health Research; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; Ontario Research Foundation","keywords":"Transfection; Gene delivery; Nanoparticle; Pulmonary surfactant; Phospholipid; DNA; Nanotechnology; Materials science; Biophysics; Chemistry; Gene; Membrane; Biology; Biochemistry","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":[0.0001741151,0.0001364278,0.0001536323,0.00002575933,0.00007818435,0.00001690416,0.0001619718,0.0001729966,0.0001155065],"category_scores_gemma":[0.00003934931,0.0001263123,0.00008654698,0.00009366799,0.0002168797,0.000007388709,0.00004529543,0.00006636648,0.00001907035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008062661,"about_ca_system_score_gemma":0.00003305674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002881673,"about_ca_topic_score_gemma":0.000009893351,"domain_scores_codex":[0.9990218,0.00005479109,0.0002528144,0.0002933822,0.0001284511,0.000248821],"domain_scores_gemma":[0.9994789,0.00001048376,0.00004382108,0.0002463137,0.0001491049,0.00007136501],"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":[0.0001785691,0.00007027628,0.0003370983,0.000008329762,0.00003011589,5.009037e-7,0.0001129683,0.0001218528,0.9972645,0.00008678971,0.001015565,0.0007734546],"study_design_scores_gemma":[0.0003466459,0.0006144175,0.00003140085,0.00002564783,0.00002343967,0.000004408962,0.0001127673,0.0108077,0.9872071,0.0001133753,0.0005611049,0.0001520092],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.989265,0.000232207,0.009230977,0.00005027404,0.0001963734,0.00009228764,0.00003291685,0.0000182079,0.0008817303],"genre_scores_gemma":[0.9991257,0.0001017566,0.0003249206,0.00009259157,0.0001171967,0.000006324077,0.00005885647,0.00001987429,0.0001527628],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01068585,"threshold_uncertainty_score":0.5150865,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01047853006542836,"score_gpt":0.2441809089895384,"score_spread":0.23370237892411,"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."}}