Research on the Scientific Evolution of the Flavonoid Agathisflavone
Bibliographic record
Abstract
PURPOSE: Flavonoids are a group of secondary metabolites of the polyphenols class present in several plant species. Among them, the biflavonoid agathisflavone is of interest since it bears several biological effects that include: antiviral, antitumoral, antiprotozoal and neurogenic actions. In this sense, this study aims to use the important tool of scientific prospecting to assess the level of research development concerning the flavonoid agathisflavone. METHODS: The experimental design was carried out through strategic reach with keywords on the PubMed (National Center for Biotechnology Information - NCBI) and Science Direct platforms. The articles were compiled and exported to Microsoft Office Excel 2007, where they were analyzed, stored and distributed in charts organized as to different countries, year of publication of scientific articles and journals RESULTS: The prospective research resulted in the identification of 81 scientific productions, published in several journals, submitted by different countries, in several areas of medical domain and in different years of publication over the last 50 years (1965 - 2018). It was also possible to investigate the advances in the study of agathisflavone for the development of new therapeutics. CONCLUSION: Although agathisflavone has been known in the literature since at least 1969, only 23 of the eligible articles found evaluated its possible therapeutic effects. The demonstrated biological activities of agathisflavone range from antiprotozoal to neurogenesis and neuroprotection, however, the molecule needs to be better studied at the in vivo and human level.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".