Wetland-use Change on Ecological Impact: A Topic-based Bibliometric Analysis
Bibliographic record
Abstract
This study employs a bibliometric approach to analyze the global trends in wetlanduse change research published in the Scopus database between 2003 and 2023. Over 396 articles were examined, revealing a staggering sixfold increase in annual publications and a ninefold surge in citations during this period. The USA dominated global research output, followed by Canada and the UK. Moreover, international collaboration showed remarkable growth. Keyword analysis highlighted “water” as a central theme, appearing amongst the top keywords in various categories. Notably, “constructed wetland biodiversity” emerged as a burgeoning research area. This analysis demonstrates the effectiveness of title, author keyword, and keyword plus approaches for mapping the landscape of wetland research. These findings suggest an increasingly vibrant and collaborative field, with water quality and constructed wetland biodiversity demanding particular attention. Moving forward, addressing critical research gaps in areas like climate change impacts and effective wetland management practices will be crucial for the sustainable future of these vital ecosystems. Keywords: bibliometric analysis, ecological impact, wetland-use
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.217 | 0.235 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".