{"id":"W2051735108","doi":"10.9734/ejmp/2014/10322","title":"Optimization of Water Based-extraction Methods for the Preparation of Bioactive-rich Ginger Extract Using Response Surface Methodology","year":2014,"lang":"en","type":"article","venue":"European Journal of Medicinal Plants","topic":"Ginger and Zingiberaceae research","field":"Pharmacology, Toxicology and Pharmaceutics","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Response surface methodology; Extraction (chemistry); Water extraction; Chromatography; Chemistry; Traditional medicine; Medicine","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.0352946,0.0001323194,0.000354327,0.000220562,0.0001522654,0.000008568856,0.0002518197,0.00008566165,0.0002073842],"category_scores_gemma":[0.001734199,0.00007998681,0.0001116636,0.0001101319,0.0001823274,0.0001438411,0.0000283141,0.0005756927,0.000002267962],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004043503,"about_ca_system_score_gemma":0.0001000244,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004411651,"about_ca_topic_score_gemma":3.671397e-7,"domain_scores_codex":[0.9864231,0.01220847,0.0007244869,0.0001381586,0.0002521744,0.0002536548],"domain_scores_gemma":[0.9893432,0.009290474,0.000696107,0.0001345246,0.0004307859,0.0001048971],"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":[0.01429769,0.0001204219,0.0004507015,0.00006220342,0.0001932416,0.0000123822,0.001297073,0.2554733,0.7027738,0.000006130429,0.000254706,0.02505828],"study_design_scores_gemma":[0.002414004,0.001501276,0.002172579,0.00009743118,0.0004026492,0.0002854693,0.0003517837,0.3265869,0.6547825,0.00003301668,0.01126118,0.0001111224],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4334295,0.0004292231,0.5646708,0.0004870376,0.0006497444,0.0001609659,0.000006359664,0.000004335455,0.0001620607],"genre_scores_gemma":[0.8719375,0.0001032298,0.1275067,0.0001228093,0.0002446749,7.666941e-7,0.000004884503,0.00002057374,0.00005886185],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.438508,"threshold_uncertainty_score":0.9933672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3513750628447747,"score_gpt":0.5667678771465022,"score_spread":0.2153928143017276,"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."}}