{"id":"W4200126254","doi":"10.1080/10408398.2021.2013771","title":"Green extraction and characterization of leaves phenolic compounds: a comprehensive review","year":2021,"lang":"en","type":"review","venue":"Critical Reviews in Food Science and Nutrition","topic":"Phytochemical and Pharmacological Studies","field":"Medicine","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Nutraceutical; Biomass (ecology); Agriculture; Extraction (chemistry); Ingredient; Business; Sustainability; Health benefits; Biotechnology; Environmental science; Pulp and paper industry; Waste management; Engineering; Traditional medicine; Food science; Chemistry; Medicine; Agronomy","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":[0.00055892,0.0002385038,0.002201484,0.0001269053,0.00009669019,0.00002131768,0.00008895123,0.0001585289,0.00001959642],"category_scores_gemma":[0.001077224,0.000167084,0.0001589965,0.0009650951,0.0009281794,0.0001798629,0.0001158151,0.0004387258,0.000003191034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007099831,"about_ca_system_score_gemma":0.00008823082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001812656,"about_ca_topic_score_gemma":3.243482e-7,"domain_scores_codex":[0.998,0.0001913902,0.0008003113,0.0004738386,0.0003056769,0.000228786],"domain_scores_gemma":[0.9988476,0.0003253343,0.0001757735,0.0001411742,0.0003458245,0.0001643092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000007141324,0.0002564574,0.000002017037,0.2375502,0.00001096339,0.0000058504,0.00001073497,5.366501e-11,0.003812026,0.0002790287,0.0001155047,0.7579501],"study_design_scores_gemma":[0.0001836592,0.0002912754,0.00005122848,0.2031892,0.0004223757,0.0001269787,0.000007321519,0.000001172848,0.0001434723,0.0001934671,0.7952463,0.0001435075],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0004178775,0.9969316,0.000006486817,0.0008178389,0.00006509398,0.001612227,0.00002774209,0.000009050943,0.0001121217],"genre_scores_gemma":[0.0003156375,0.9982612,0.0001365934,0.0008253288,0.000101857,0.0002896811,0.00005857775,0.000007049829,0.000004118975],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7951308,"threshold_uncertainty_score":0.6813488,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1936410397202453,"score_gpt":0.4517443933892175,"score_spread":0.2581033536689721,"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."}}