{"id":"W2943159568","doi":"10.3390/pharmaceutics11050215","title":"In Silico Prediction of Plasma Concentrations of Fluconazole Capsules with Different Dissolution Profiles and Bioequivalence Study Using Population Simulation","year":2019,"lang":"en","type":"article","venue":"Pharmaceutics","topic":"Drug Solubulity and Delivery Systems","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Bioequivalence; Cmax; Dissolution; Population; Dissolution testing; Pharmacokinetics; Bioavailability; Chemistry; Chromatography; Confidence interval; Pharmacology; Mathematics; Biopharmaceutics Classification System; Statistics; Medicine; Organic chemistry","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008405073,0.0004861618,0.0006020273,0.0004661383,0.0002498926,0.0005952743,0.0004941219,0.001092376,0.001105253],"category_scores_gemma":[0.00258218,0.0003170064,0.0008767997,0.0002504395,0.0003110615,0.0003186168,0.0003631399,0.0006408488,0.0001010476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008098484,"about_ca_system_score_gemma":0.0009481265,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01297547,"about_ca_topic_score_gemma":0.004522069,"domain_scores_codex":[0.9997618,0.0001109703,0.000011301,0.00004061005,0.00003485072,0.00004052335],"domain_scores_gemma":[0.9979645,0.001651951,0.0001392966,0.00003704916,0.0001587205,0.0000484825],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009319072,0.00006282634,0.001693301,0.00002162382,0.00002932852,0.00003536787,0.00001486005,0.9954153,0.000873419,0.0004072273,0.00007195214,0.001281649],"study_design_scores_gemma":[0.00001397775,0.00007460862,0.0003899373,0.000002275438,0.00001356264,0.000007313043,0.000007303049,0.9988129,0.00046506,0.0001231796,0.00008632363,0.000003591341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9481463,0.0002937893,0.04708298,0.0002097472,0.00003580176,0.0001018694,0.0003261342,0.0001005248,0.003702773],"genre_scores_gemma":[0.9930161,0.0001097512,0.005748331,0.00003289113,0.000005078307,0.00009421846,0.0001864163,0.000007783052,0.0007994558],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01297547,"threshold_uncertainty_score":0.02579987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1389759494146013,"score_gpt":0.4244238686215542,"score_spread":0.2854479192069529,"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."}}