Bibliographic record
Abstract
In the final quarter of 2024 four major environment meetings were convened. These included the “triple COP” – separate meetings of the 16th Conference of the Parties to the Convention on Biological Diversity (CBD COP-16), the 29th Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC COP-29), and the 16th Conference of the Parties to the United Nations Convention on Desertification (UNCCD COP-16); and the 11th meeting of the Plenary of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES).The biennial CBD COP is arguably the most significant biodiversity meeting on the global calendar, while the biennial UNCCD COP covers various topics of direct relevant to biodiversity and the UNCCD has followed the CBD lead in many respects including by embracing CBD biodiversity targets. Meetings of the IPBES Plenary are arguably the second most important biodiversity meeting on the global calendar. None of these meetings attract as much public attention, or as many delegates, as the UNFCCC COP (66,000 registrations for COP-29) they still draw substantial participation, with about 23,000 registrations for CBD COP-16, about 20,000 for UNCCD COP-16, and about 900 for IPBES-11. So, what has been all the convening and negotiation around biodiversity focused on, and what are the links between these meetings? Here we focus on the two meetings that are most relevant to biodiversity: CBD COP-16 and IPBES-11.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.007 |
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; both teacher heads agree on what is shown here.
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".