{"id":"W2800933382","doi":"10.1002/jsde.12033","title":"Physicochemical Characterization of Chrysin‐Derivative‐Loaded Nanostructured Lipid Carriers with Special Reference to Anticancer Activity","year":2018,"lang":"en","type":"article","venue":"Journal of Surfactants and Detergents","topic":"Advancements in Transdermal Drug Delivery","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Department of Science and Technology, Government of Kerala; Department of Science and Technology, Ministry of Science and Technology, India","keywords":"Chemistry; Chrysin; Differential scanning calorimetry; Zeta potential; Monolayer; Dynamic light scattering; Nuclear chemistry; Chemical engineering; Chromatography; Organic chemistry; Nanoparticle; Biochemistry; Flavonoid","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":[0.0001511342,0.000185532,0.0003715417,0.00008785569,0.0001068234,0.00001181274,0.0001644954,0.0001281332,0.0005342525],"category_scores_gemma":[0.00003373543,0.0001450181,0.00004579511,0.0001894307,0.0002848427,0.0003047472,0.00004430153,0.0003375009,0.000004868611],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005067122,"about_ca_system_score_gemma":0.00008024459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003518337,"about_ca_topic_score_gemma":0.000003477636,"domain_scores_codex":[0.9987774,0.0001151368,0.0003777971,0.0001886319,0.0002868447,0.0002542236],"domain_scores_gemma":[0.9988547,0.00004594741,0.0004283615,0.0001002279,0.0003416689,0.0002291011],"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":[0.004142324,0.0001251504,0.01345696,0.00002793694,0.000197485,0.00001018867,0.000718312,0.00001101529,0.969147,0.000006791707,0.0001110417,0.01204579],"study_design_scores_gemma":[0.001557539,0.0006275845,0.1008274,0.00006291788,0.00009417806,0.00001962594,0.00003168048,0.00006002825,0.8889577,0.0000228578,0.007577389,0.0001610769],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975243,0.00001564624,0.0007806161,0.0001178981,0.001045932,0.0001642398,0.0001156669,0.000005679026,0.0002300633],"genre_scores_gemma":[0.9983831,0.0001773699,0.0003683956,0.0003498502,0.0006508389,0.000001180708,0.000003894234,0.00001532805,0.00005001314],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08737044,"threshold_uncertainty_score":0.5913665,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06430343729110949,"score_gpt":0.3806370142294805,"score_spread":0.3163335769383711,"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."}}