Bibliographic record
Abstract
The Kunming–Montreal Global Biodiversity Framework (the Framework) was adopted at the Fifteenth Meeting of the Conference of the Parties (COP15) to the 1992 Convention on Biological Diversity (CBD) on December 19, 2022. Despite the efforts made under the CBD, biodiversity loss has continued at an alarming rate, and the targets set under the Convention's Strategic Plan for Biodiversity 2011–2020 were not fully achieved. In 2018, the CBD Parties therefore adopted a decision to develop a post-2020 global biodiversity framework to guide international efforts towards the conservation and sustainable use of biodiversity over the next decade. The Framework, the adoption of which was delayed by two years by the COVID-19 pandemic, succeeds and replaces the 2011–2020 Strategic Plan for Biodiversity and its accompanying Aichi Targets. The Framework includes four overarching goals and twenty-three accompanying targets to be achieved by 2030, together with four long-term goals to achieve the 2050 Vision for Biodiversity.
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.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".