{"id":"W4392373952","doi":"10.3390/molecules29051137","title":"Agave angustifolia Haw. Leaves as a Potential Source of Bioactive Compounds: Extraction Optimization and Extract Characterization","year":2024,"lang":"en","type":"article","venue":"Molecules","topic":"Phytochemicals and Antioxidant Activities","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Ministry of Agriculture and Forestry; Agriculture Food and Rural Development; University of Alberta","funders":"Consejo Nacional de Ciencia y Tecnología","keywords":"ABTS; DPPH; Maceration (sewage); Chemistry; Flavonoid; Extraction (chemistry); Polyphenol; Chromatography; Supercritical carbon dioxide; Supercritical fluid extraction; Supercritical fluid; Food science; Antioxidant; Organic chemistry; Materials science","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":[0.00005031601,0.0001241739,0.0001866439,0.0001371803,0.00004522297,0.00005874165,0.00002513152,0.0000844587,0.00004256232],"category_scores_gemma":[0.00003190759,0.0001129622,0.00006563449,0.0001266969,0.00009855893,0.0002358217,0.00001858189,0.0001166839,0.000004705999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000243608,"about_ca_system_score_gemma":0.00004098926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002751562,"about_ca_topic_score_gemma":4.357803e-7,"domain_scores_codex":[0.9993104,0.00002328395,0.0001759897,0.0002144131,0.0001599097,0.0001159832],"domain_scores_gemma":[0.9996909,0.00003387422,0.00007598878,0.0000863394,0.00006082413,0.00005206962],"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":[0.0001431439,0.00009544973,0.0001322425,0.0001876964,0.0000707556,0.00003303794,0.0002781745,0.00013912,0.991182,0.0001562023,0.0000363046,0.007545915],"study_design_scores_gemma":[0.0004414929,0.0002628155,0.01024519,0.0005613082,0.0002156706,0.0003503815,0.0004857962,0.06668571,0.9197533,0.0001631876,0.0006420295,0.0001931421],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8825525,0.0006261591,0.1153747,0.0003384884,0.0001081661,0.0001746058,0.00002125546,0.00008505135,0.000719076],"genre_scores_gemma":[0.997587,0.0002732289,0.001379639,0.00005451631,0.0001420442,0.000008274568,0.0001398979,0.00002403344,0.0003913214],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1150345,"threshold_uncertainty_score":0.4606464,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007540438355204788,"score_gpt":0.2568198573429358,"score_spread":0.249279418987731,"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."}}