Advancements in Mine Closure and Ecological Reclamation: A Comprehensive Bibliometric Overview (1980–2023)
Why this work is in the frame
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Bibliographic record
Abstract
Faced with the ongoing energy transition and the escalating fragility of our natural ecosystems, ecological reclamation emerges as an imperative necessity. Investigation within this field has been in progress since the early 20th century. To gauge the advancements in this realm, elucidate the evolving research trends, and emphasize pertinent metrics, it is essential to perform a comprehensive overview of the subject. Undertaking this bibliometric study is necessary to clarify research’s current state of play, grasp research hotspots, showcase outstanding researchers, and predict future research trends. In this work, 40,386 articles were retrieved from the Scopus and Web of Science databases, and bibliometric analysis was carried out using the Biblioshiny R package (Version 4.0.0, K-Synth Srl, Naples, Italy), and Python (PyCharm Community Edition 2023.2.1)o understand the progress in this research field from 1980 to 2023. The findings reveal a consistent upward trend in the publication rate within the field of mine closure and ecological reclamation over this timeframe, culminating in 6705 articles by 2022. Notably, authors and institutions from China have taken the lead, followed closely by those from the USA and Canada in terms of article publications. This prominence can be attributed to these countries’ rapid economic growth and energetic transition, which has frequently come at the expense of environmental quality, and a rise in reclamation challenges. In this sense, the circular economy has risen in force recently, which highlights the withdrawal of the old linear economy. In coming research on mine closure and ecological reclamation, multi-scale ecological reclamation research should be reinforced, and social and economic concerns should be integrated. This study pinpointed current research hotspots and forecasted potential future research areas, providing a scientific baseline for future studies in mine closure and ecological reclamation.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.007 | 0.018 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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