{"id":"W2903502026","doi":"10.1021/acs.molpharmaceut.8b00874","title":"Microfluidic Manufacturing of SN-38-Loaded Polymer Nanoparticles with Shear Processing Control of Drug Delivery Properties","year":2018,"lang":"en","type":"article","venue":"Molecular Pharmaceutics","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; University of Victoria","keywords":"Microfluidics; Nanoparticle; Drug delivery; Polymer; Materials science; Materials processing; Nanotechnology; Drug; Shear (geology); Chemistry; Composite material; Pharmacology; Process engineering; Engineering","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":[0.0004532157,0.0006028736,0.0003445721,0.0002678056,0.0001672092,0.000308396,0.0003393604,0.0002607059,0.0006034464],"category_scores_gemma":[0.0004427854,0.0003772223,0.0003816193,0.0001809541,0.0002522945,0.0002469021,0.0002507348,0.0003940561,0.000290904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005940027,"about_ca_system_score_gemma":0.0003307084,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004984831,"about_ca_topic_score_gemma":0.0006769739,"domain_scores_codex":[0.9997284,0.00002670503,0.00004444067,0.00009262328,0.00006630683,0.00004161649],"domain_scores_gemma":[0.9997608,0.00006838443,0.00009002768,0.00002923981,0.00003169785,0.00001983722],"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":[0.00003874227,0.00001368327,0.00007579302,0.00002664951,0.000003158452,0.00001751099,0.00001465988,0.0002763453,0.9982237,0.00007596894,0.00002197047,0.001211692],"study_design_scores_gemma":[0.000009418602,0.0000835146,0.0004178788,0.000001994415,0.000006528955,0.0000200756,0.000002667186,0.002262277,0.9965106,0.00001620903,0.0006632242,0.000005635905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9434978,0.0009788221,0.05241598,0.0001367801,0.0001092753,0.0003109048,0.0005247438,0.0005810662,0.001444668],"genre_scores_gemma":[0.8937978,0.0008219516,0.1022708,0.00006877556,0.00003257734,0.0004736372,0.0004546511,0.00009417976,0.001985562],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006034464,"threshold_uncertainty_score":0.004309833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01518367865746596,"score_gpt":0.2409818377179403,"score_spread":0.2257981590604743,"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."}}