Bibliometric insights and content analysis of diatom paleolimnology in lakes: Global perspectives and Indonesian contributions over the last decade
Bibliographic record
Abstract
This study evaluates global scientific publications on diatom-based lake paleolimnology from 2014 to 2024, with a focus on Indonesia's contributions, using bibliometric and content analysis of Scopus data. A total of 378 publications were identified, with relatively stable annual output. The Journal of Paleolimnology is the leading publication outlet, and Agricultural and Biological Sciences is the most studied subject area. Canada, the United States, and China dominate in publication volume, with Canadian authors being the most influential. Indonesia's research remains limited to a few lakes (Towuti, Rawapening, and Warna), indicating challenges but also potential for expansion. Keyword analysis revealed seven clusters centered on paleolimnology and diatoms. Underexplored research areas include microenvironment, miocene, modern analogs, modern sediments, nutrient limitation, siliceous components, and Patagonian palaeoenvironments. These themes suggest promising directions such as investigating Miocene microhabitats, improving ecological reconstructions through modern analog comparisons, and studying nutrient dynamics and silica availability, which are crucial for diatom growth and lake productivity. The study's findings aim to inform and enhance paleolimnology research in Indonesia and foster greater international collaboration.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.006 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.098 | 0.151 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".