Kunming-Montreal Global Biodiversity Framework and the construction of the national botanical garden system
Bibliographic record
Abstract
The adoption of the Kunming-Montreal Global Biodiversity Framework by the 15th Meeting of Conference of the Parties to the Convention on Biological Diversity signifies another collective effort by the international community to tackle the ongoing biodiversity crisis. It also marks the beginning of China's leadership in global environmental governance. The establishment of the national botanical garden system serves as an innovative practice to biodiversity conservation. This article aims to examine the potential of the national botanical garden system in facilitating the implementation of the Kunming-Montreal Framework in China. Methods: Through an analysis of the Kunming-Montreal Framework's long-term objectives and specific targets for the year 2030, this study identifies the essential inquiries and conservation actions that can be implemented by the national botanical garden system in China. Results: This study outlines 26 research questions and 27 conservation actions that can be undertaken by the national botanical garden system. Furthermore, it highlights 7 priority actions that should be given immediate attention. These include conducting a thorough survey of plant species, examining the genetic diversity of nationally protected plants, implementing conservation strategies to mitigate plant extinctions in critical biodiversity areas, executing ecological restoration plans, conducting research on climate change adaptation, promoting education on conservation and sustainable development, and fostering international cooperation in biodiversity conservation.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".