The Ethnopharmacological Literature: An Analysis of the Scientific Landscape in the Cerrado in Central-Western Brazil
Bibliographic record
Abstract
Research on pharmacology and phytochemistry originating from medicinal plants has resulted in various publications highlighting the Cerrado in central-western Brazil, which has a remarkable diversity of plant species. The reserve area selected was the Cerrado stricto sensu settlement “17 April”, Mato Grosso do Sul (MS), Brazil. However, no ethnopharmacological review focusing on the plants present in the reserve area exists, even though the consumption of medicinal plants is a widespread practice. The aims of this study were to 1) survey and document the medicinal plants present in the reserve area; 2) provide an overview of recent ethnopharmacological, phytochemical and pharmacological studies of these species; and 3) provide insight for future studies. A literature search was conducted, and relevant information was collected from authentic resources using databases such as Science Direct, PubMed, Google Scholar, Web of Science and Scopus, as well as peer reviewed articles, books and theses. Eighty-nine species belonging to 39 different families were found; the most abundant were Fabaceae (n = 13), Myrtaceae (n = 7), Rubiaceae (n = 7) and Bignoniaceae (n = 5). In terms of it empirical use, the most utilized parts were leaves (41%), bark (22%) and roots (15%). The most widespread traditional use, according to the literature review of the following plants involves the treatment of gastro-intestinal system diseases (41 spp). Chemical studies reported a high presence of terpene, phenol, and alkaloid classes. Only three are listed in the RENISUS: Casearia sylvestris, Copaifera langsdorffii and Stryphnodendron adstringens. This study demonstrated a large number of medicinal plants in an area of the Cerrado in the state of Mato Grosso do Sul, Brazil. Noting the importance of biodiversity for the development of new pharmacological approaches, many studies prove the empirical use of medicinal plants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.020 | 0.036 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".