{"id":"W4386033718","doi":"10.53811/ijtcmr.1315159","title":"Preparation of Centella asiatica (L). and Hypericum perforatum (St. John's Wort) Plant Extracts and Development of Anti-Aging Herbal Cream Formulations","year":2023,"lang":"en","type":"article","venue":"International Journal of Traditional and Complementary Medicine Research","topic":"Medicinal Plants and Neuroprotection","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Düzce Üniversitesi","keywords":"Hypericum perforatum; Centella; Traditional medicine; Hypericin; Hyperforin; Ingredient; Chemistry; Extraction (chemistry); Chromatography; Hypericum; Food science; Biology; Pharmacology; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001220126,0.0000962073,0.0002804266,0.0006227006,0.0001432196,0.00001416904,0.00007998986,0.00002808159,0.0002010469],"category_scores_gemma":[0.0001425654,0.00007111172,0.00002663934,0.0001748276,0.0002554953,0.0001523557,0.00004138598,0.0002628922,6.08385e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004528748,"about_ca_system_score_gemma":0.0001941143,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005898711,"about_ca_topic_score_gemma":0.00001451755,"domain_scores_codex":[0.9976599,0.00007069202,0.0006825691,0.0001417708,0.001294833,0.0001501983],"domain_scores_gemma":[0.9986049,0.0004421205,0.0002343574,0.00005199392,0.0005058651,0.0001607742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.01286569,0.004943031,0.22608,0.003769842,0.004689562,0.002196384,0.02435775,0.0002297305,0.4491952,0.01932133,0.0572037,0.1951478],"study_design_scores_gemma":[0.005957336,0.004677935,0.9424438,0.002726435,0.0001302043,0.004171484,0.004256736,0.004268054,0.01223817,0.002436932,0.0165228,0.0001701006],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9936206,0.0002999396,0.0001996011,0.005075084,0.00018403,0.0002151029,0.00007935492,0.000004896794,0.0003214319],"genre_scores_gemma":[0.9975012,0.0008654066,0.0008558473,0.00006756643,0.0003908065,0.000004320295,0.0002723768,0.000007029396,0.00003545971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7163638,"threshold_uncertainty_score":0.2899852,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1937523228206385,"score_gpt":0.4171218246195669,"score_spread":0.2233695017989284,"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."}}