{"id":"W3132128830","doi":"10.1186/s40538-020-00203-6","title":"Optimization of subcritical water extraction of phenolic compounds from Ziziphus jujuba using response surface methodology: evaluation of thermal stability and antioxidant activity","year":2021,"lang":"en","type":"article","venue":"Chemical and Biological Technologies in Agriculture","topic":"Ziziphus Jujuba Studies and Applications","field":"Agricultural and Biological Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Chemistry; Ziziphus jujuba; Gallic acid; Ferulic acid; Chlorogenic acid; Response surface methodology; Polyphenol; Hydroxytyrosol; Rutin; Solvent; Antioxidant; Caffeic acid; Extraction (chemistry); Food science; Emulsion; Chromatography; Organic chemistry; Botany","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":[0.0001797328,0.0005150781,0.0003383984,0.0002983174,0.0001571421,0.0002544605,0.0001675204,0.00030579,0.0006154232],"category_scores_gemma":[0.0001739074,0.0001495193,0.0003381566,0.0002439145,0.0001498573,0.0001904949,0.0001219273,0.0002436351,0.0002231422],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001504598,"about_ca_system_score_gemma":0.0001570249,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007423816,"about_ca_topic_score_gemma":0.001520807,"domain_scores_codex":[0.999871,0.00002740819,0.000009950645,0.0000237326,0.0000516291,0.00001635616],"domain_scores_gemma":[0.9999411,0.0000149664,0.00001642293,0.000003584473,0.00001791558,0.000005957254],"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":[0.00003176856,0.00001705587,0.00007775059,0.00005900901,0.000004542993,0.00001637437,0.000006536728,0.00009027935,0.9988194,0.00001059774,0.00001603619,0.0008505478],"study_design_scores_gemma":[0.00001116346,0.0002938544,0.00357733,0.000008681801,0.00002564485,0.00006675948,0.00002227287,0.00148531,0.9935873,0.00001609282,0.0008971146,0.000008418494],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988525,0.002407169,0.007554847,0.0001047867,0.00002582604,0.0001116875,0.0002552262,0.0000658377,0.0009496922],"genre_scores_gemma":[0.9849745,0.001804977,0.0109384,0.00005895989,0.00001147108,0.0001199395,0.0003343508,0.00002012321,0.001737318],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007423816,"threshold_uncertainty_score":0.002058804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1220235071593981,"score_gpt":0.31607598908291,"score_spread":0.1940524819235119,"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."}}