{"id":"W1969641539","doi":"10.1016/j.ijpharm.2011.12.016","title":"Preparation of vitamin E loaded nanocapsules by the nanoprecipitation method: From laboratory scale to large scale using a membrane contactor","year":2011,"lang":"en","type":"article","venue":"International Journal of Pharmaceutics","topic":"Lipid Membrane Structure and Behavior","field":"Biochemistry, Genetics and Molecular Biology","cited_by":149,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Agence Universitaire de la Francophonie","keywords":"Nanocapsules; Zeta potential; Contactor; Chromatography; Membrane; Materials science; Vitamin E; Chemistry; SCALE-UP; Antioxidant; Nanotechnology; Nanoparticle; Organic chemistry; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003470189,0.0001152877,0.0001511274,0.00006466411,0.0000358197,0.00001997283,0.0003584576,0.00008615136,0.00008215603],"category_scores_gemma":[0.00005463651,0.00008766131,0.0001190608,0.00007164299,0.00003625101,0.00002545718,0.00006193527,0.000110683,0.000001836404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003168024,"about_ca_system_score_gemma":0.0001033086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003016505,"about_ca_topic_score_gemma":0.00002247181,"domain_scores_codex":[0.9988711,0.0001362154,0.0004124483,0.0001341312,0.000330542,0.0001155128],"domain_scores_gemma":[0.9987044,0.00002987276,0.0003897229,0.0001221744,0.000674565,0.00007927712],"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":[0.0005053374,0.00009348281,0.001375319,0.000004778863,0.0001829719,0.000002156174,0.001474973,0.0000631953,0.9950016,0.000005694513,0.0002033114,0.001087228],"study_design_scores_gemma":[0.0009360763,0.0001131089,0.0007079217,0.00002603214,0.0001208349,0.00002027545,0.0003864324,0.0001559084,0.9873459,0.00001241678,0.01008071,0.00009443521],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9861803,0.0002093444,0.01186428,0.0000859041,0.001050712,0.0001263165,0.0004270729,0.000002754487,0.0000533376],"genre_scores_gemma":[0.9896237,0.00007361625,0.009306666,0.0003975048,0.0004703888,0.000001964257,0.00005856049,0.00001442443,0.00005312583],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0098774,"threshold_uncertainty_score":0.3574724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02919887004061283,"score_gpt":0.3723261807570775,"score_spread":0.3431273107164646,"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."}}