{"id":"W2031727690","doi":"10.1016/j.ijpharm.2012.11.033","title":"Food proteins as novel nanosuspension stabilizers for poorly water-soluble drugs","year":2012,"lang":"en","type":"article","venue":"International Journal of Pharmaceutics","topic":"Drug Solubulity and Delivery Systems","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":101,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"National Key Research and Development Program of China; Fudan University","keywords":"Bioavailability; Sonication; Particle size; Dissolution; Whey protein; Denaturation (fissile materials); Chemistry; Particle (ecology); Chemical engineering; Particle-size distribution; Solubility; Particle aggregation; Protein aggregation; Chromatography; Whey protein isolate; Stabilizer (aeronautics); Nanoparticle; Drug; Materials science; Nanotechnology; Organic chemistry; Nuclear chemistry; Biochemistry; Pharmacology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002550496,0.0002977184,0.0003961487,0.0002893134,0.0002059237,0.0000734822,0.0007860073,0.0002948812,0.0009743767],"category_scores_gemma":[0.0002048893,0.0002418535,0.0003808599,0.0001060524,0.0001574074,0.0007828256,0.0001558997,0.0008227071,0.0001758499],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003120138,"about_ca_system_score_gemma":0.0001914133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001437022,"about_ca_topic_score_gemma":0.00000417979,"domain_scores_codex":[0.9970794,0.0002460632,0.001011529,0.0002071365,0.0007445437,0.0007113253],"domain_scores_gemma":[0.9969798,0.0004456502,0.0005696754,0.0001470089,0.001305282,0.0005525991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.007007007,0.003280678,0.004975663,0.0001731073,0.002682521,0.00006031334,0.009428012,0.001680082,0.9444085,0.004767148,0.006890858,0.01464607],"study_design_scores_gemma":[0.004568068,0.0004205531,0.00006353513,0.00004085849,0.0001948933,0.0005520661,0.0006977899,0.00111538,0.4624947,0.0003574574,0.5292512,0.0002434557],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.961891,0.001199924,0.003667179,0.003797778,0.02476447,0.0009062059,0.0001680064,0.00005646788,0.003548948],"genre_scores_gemma":[0.9923291,0.0001699809,0.001049173,0.002570591,0.002769801,0.00003168701,0.00003261719,0.00004572116,0.001001391],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5223603,"threshold_uncertainty_score":0.9999388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1486240921900985,"score_gpt":0.4486651080111666,"score_spread":0.3000410158210681,"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."}}