A Bibliometric Review of the Impacts of Logging in Forests in Semi-Arid Zones
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
Forest massifs in semi-arid zones play an essential role in maintaining ecological balances and the livelihood of local communities. However, unsustainable logging in these regions can have devastating ecological, and socio-economic consequences. This bibliometric review aims to synthesize the available evidence regarding the impacts of logging in semi-arid ecosystem. Analysis of publication trends reveals a significant increase in research from 2008, reflecting a growing awareness of the issues related to sustainable forest management. The United States, Canada, Australia and China the most prominent countries in this field. The bibliometric analysis of the highlights major concerns related to climate change, clear-cutting, interactions with demographic dynamics and biogeochemical cycles. However, gaps remain, including a lack of data specific to semi-arid areas, limited understanding of the complex interactions between different dimensions of impacts, and insufficient integration of local perspectives and traditional knowledge. This review highlights the need to continue interdisciplinary and collaborative research efforts to ensure sustainable management of semi-arid forests in the face of current and future environmental challenges.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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: Review About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.027 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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