Exploring global trends in scientific research on <i>Rubus glaucus</i> Benth.: A comprehensive analysis integrating bibliometrics, LDA, and HJ-Biplot
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background Rubus glaucus Benth, called Andean blackberry, is a species of significant economic and ecological importance. Despite its relevance, scientific research on this plant remains fragmented and scattered across disciplines. Objective This study aims to systematically assess the state of scientific knowledge on R. glaucus, identifying research trends, collaborations, and thematic evolutions within the global research community. Methods We employed a comprehensive bibliometric analysis integrated with Latent Dirichlet Allocation (LDA) and HJ-Biplot methodologies to analyze publications from Scopus and Web of Science databases. Results Our findings reveal a substantial increase in research interest from the 1990s, reaching a peak in the early 2010s before a recent decline. The study highlights significant contributions from the United States, the United Kingdom, Canada, Italy, and Colombia, with notable international collaborations. Thematic analysis underscored the ecological role, nutritional benefits, and genetic improvement of R. glaucus as focal areas of research, pointing out gaps in pest management and sustainable cultivation practices. Conclusions This comprehensive bibliometric analysis offers valuable insights into the research landscape of R. glaucus, underscoring the need for focused research efforts on underexplored areas. The study lays the groundwork for future research directions, encouraging interdisciplinary collaboration to leverage the plant's full potential for agricultural innovation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.008 | 0.090 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it