Jiufeng Protected Area Biodiversity Threats Assessment
Bibliographic record
Abstract
Located in the East of Wuhan City, Jiufeng Protected area is endowed with a rich biodiversity in diversitylandscape (Metasequoia forests, forest ponds, pine forest, Wetland pine, fir, cedar forest, Liquidambar forests,oak forests massoniana and lobular, Lin and mushroom). The objectives of this study were to assess andunderstand the biodiversity threats, evaluate activities, help prioritize and anticipate what threats might becomemore severe in the future. Threat assessment was based on a review of peer articles and secondary data sourcessuch as key informant interviews. Interviews with local and provincial authorities and visits in the field were heldto gather information on Jiufeng protected area resources and biodiversity threats. This research was carried out onJune 2009. The Interviews, the literature review and field report showed that the biodiversity is threatened by avariety of human activities and natural factors such as climate change and invasive alien species. These threatscan cause the biodiversity loss. In Jiufeng Protected Area, human activities such as land use and land coverchange, industrialization and pollution, tourism and recreation constitute threats for biodiversity.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".