{"id":"W2072317402","doi":"10.3109/02652048.2014.944951","title":"Polymer assisted entrapment of netilmicin in PLGA nanoparticles for sustained antibacterial activity","year":2014,"lang":"en","type":"article","venue":"Journal of Microencapsulation","topic":"Advanced Drug Delivery Systems","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Technology Information, Forecasting and Assessment Council; Indian Council of Medical Research; Department of Foreign Affairs and Trade, Australian Government","keywords":"PLGA; Antibacterial activity; Entrapment; Nanoparticle; Antibacterial agent; Drug carrier; Particle size; Nuclear chemistry; Polymer; Dextran; Chemistry; Netilmicin; Chromatography; Materials science; Antibiotics; Nanotechnology; Drug delivery; Biochemistry; Bacteria; Medicine; Organic chemistry; Surgery","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":[0.00009482976,0.0002344669,0.0001618324,0.0001397819,0.00007899494,0.000184835,0.0001123251,0.0002319242,0.0003078837],"category_scores_gemma":[0.0001077988,0.00008549932,0.0001598788,0.00008141305,0.0001114459,0.0002563088,0.0001299812,0.0001834731,0.0001283618],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002634824,"about_ca_system_score_gemma":0.0001422698,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002809729,"about_ca_topic_score_gemma":0.0005673717,"domain_scores_codex":[0.9999337,0.00001151775,0.000006943715,0.00001661766,0.00001888329,0.00001243462],"domain_scores_gemma":[0.999954,0.000009103036,0.00001887968,0.000003131557,0.000009041202,0.000005929908],"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":[0.00002811953,0.00001233833,0.00005804982,0.00003159523,0.000001640187,0.00001609489,0.000004518344,0.0001587965,0.9984825,0.00002776702,0.000007668706,0.001170959],"study_design_scores_gemma":[0.000006233041,0.0001614496,0.0006163254,0.000002370453,0.000006935592,0.00004619746,0.000004319441,0.001272747,0.9971499,0.00001277622,0.0007182669,0.000002605581],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9910744,0.001094421,0.006957939,0.00005528993,0.00001461818,0.00003359717,0.0000536609,0.0000419913,0.0006741088],"genre_scores_gemma":[0.9914094,0.0004977928,0.006755461,0.00002739441,0.000006433408,0.00003518712,0.00005804774,0.00001189219,0.001198535],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0003078837,"threshold_uncertainty_score":0.0019117,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06417240728649008,"score_gpt":0.4008432058955265,"score_spread":0.3366707986090364,"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."}}