{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001086317,0.0001241209,0.0003471253,0.0001903955,0.00005201632,0.000008140665,0.0001168739,0.0001381249,0.00005210656],"category_scores_gemma":[0.0001274357,0.0001105923,0.0001329606,0.0001414395,0.00005646704,0.0002066796,0.00001957512,0.0002030088,0.000001735211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001457632,"about_ca_system_score_gemma":0.00008019403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001400407,"about_ca_topic_score_gemma":0.00001005447,"domain_scores_codex":[0.9983852,0.0004424645,0.0006749696,0.0001148009,0.0001271193,0.0002554305],"domain_scores_gemma":[0.9984802,0.000309029,0.0008149314,0.00008538652,0.0002316065,0.00007885484],"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":[0.002288508,0.0002923764,0.02081011,0.00004661821,0.00006955043,0.000003241451,0.0003501021,0.003130039,0.9580817,0.00006421841,0.0001797874,0.01468379],"study_design_scores_gemma":[0.004265265,0.0003967555,0.08967414,0.00004248004,0.00007160569,0.00003128879,0.00009822391,0.005655083,0.8971444,0.0000945534,0.002423648,0.0001025242],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995555,0.0001906496,0.002726652,0.0002449021,0.0009346865,0.0003028772,0.00001597214,0.000006154302,0.00002307834],"genre_scores_gemma":[0.9990346,0.00002395151,0.0004781974,0.00005303415,0.000332476,0.000003766134,0.000005688725,0.00001213379,0.0000561843],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06886403,"threshold_uncertainty_score":0.4509825,"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."}}