{"id":"W1544022382","doi":"10.1111/j.1745-4530.2010.00576.x","title":"OPTIMIZATION AND SENSITIVITY ANALYSIS OF AN EXTENDED DISTRIBUTED DYNAMIC MODEL OF SUPERCRITICAL CARBON DIOXIDE EXTRACTION OF NIMBIN FROM NEEM SEEDS","year":2010,"lang":"en","type":"article","venue":"Journal of Food Process Engineering","topic":"Hibiscus Plant Research Studies","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Supercritical carbon dioxide; Computer science; Process engineering; Supercritical fluid extraction; MATLAB; Sensitivity (control systems); Context (archaeology); Extraction (chemistry); Mathematical optimization; Mathematics; Chemistry; Engineering; Chromatography","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":[0.0009604096,0.0008222187,0.0009794659,0.0005980617,0.0004548013,0.001122718,0.0005096794,0.001300137,0.001549709],"category_scores_gemma":[0.001689628,0.0005341152,0.001078158,0.0002904825,0.0006490033,0.0004413896,0.0006205986,0.0007373305,0.0001203835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001109945,"about_ca_system_score_gemma":0.0008079689,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.016022,"about_ca_topic_score_gemma":0.006744695,"domain_scores_codex":[0.9997489,0.0001013491,0.00001070197,0.00003948187,0.00005336836,0.00004621219],"domain_scores_gemma":[0.9989242,0.0008310113,0.00007842006,0.00002967782,0.0001190184,0.00001767797],"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":[0.00003990588,0.0000175005,0.0003187981,0.00003060008,0.00001931821,0.00003837005,0.00001186998,0.9969382,0.00153002,0.0002489272,0.00003783903,0.0007686007],"study_design_scores_gemma":[0.000006122169,0.00002378788,0.0002109369,0.000002499425,0.000008084771,0.000003432576,0.000006905163,0.9987139,0.0008786614,0.00007791056,0.00006444959,0.000003281768],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8151184,0.0006195179,0.1725879,0.0004437962,0.00004868965,0.0001783876,0.0003418403,0.0003002951,0.01036112],"genre_scores_gemma":[0.9949162,0.00008378024,0.003529654,0.00001490642,0.000002277003,0.00005962449,0.00006222499,0.00001232265,0.001318983],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.016022,"threshold_uncertainty_score":0.03185749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03721721593567612,"score_gpt":0.3862351006661164,"score_spread":0.3490178847304403,"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."}}