Guideline Materials and Documentation for the Genetic Diversity Indicators of the Monitoring Framework for the Kunming-Montreal Global Biodiversity Framework
Bibliographic record
Abstract
Genetic diversity is fundamental to biological diversity, vital for species’ health and adaptation to environmental change. Under the recently adopted Kunming-Montreal Global Biodiversity Framework (GBF), 196 Parties committed to report the status of genetic diversity for both wild and domesticated species. For this, three genetic diversity indicators were developed, two of which focus on processes contributing to genetic diversity conservation: ensuring that populations are large enough to maintain genetic diversity (effective population size Ne 500 indicator) and maintaining genetically distinct populations (populations maintained, PM indicator). A third indicator focuses on the number of species being monitored using DNA-based methods. Adopted by 196 CBD Parties in December 2022, GBF integrated Ne 500 and PM as headline and complementary indicators, respectively. To aid nations in quantifying these indicators, a detailed set of guideline materials was developed, encompassing species selection, data compilation, and indicator computation. These guidelines draw from the collaborative efforts of the first multinational assessment of genetic diversity indicators that was recently completed and that will be refined continually through a versioning system, as more experience is gained and shared. The materials aim to support the global monitoring framework established by the CBD and are accessible online for utilization and updates. The guidelines are available at this link.
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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 | 0.033 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.012 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.007 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.047 | 0.021 |
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".