United Nations - Convention on Biological Diversity and COP15
Bibliographic record
Abstract
With wildlife and biodiversity in an unprecedented crisis, pressure weighs heavily on the UN‘s Convention on Biological Diversity (CBD), a multilateral environmental treaty that went into effect in 1993.\nIn December 2022, the CBD’s fifteenth Conference of Parties (COP15) will convene in Montreal to adopt an updated post-2020 Global BiodiversityFramework (GBF). This Framework replaces the 2011-2020 strategic plan including the Aichi five goals and twenty targets. These targets have not been met and now need to be updated.\nPlanning for this update on a new Global Biodiversity Framework at COP15 began in 2016. COP15 was initially scheduled to be held in Kunming, China, in October 2020. However, it has been repeatedly delayed because of the pandemic. A virtual first phase of COP15 was held from October 11-15, 2021. The in-person COP15 that should adopt the new GBF is scheduled for Montreal (where the CBD secretariat is located) from December 7-19, 2022
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.029 | 0.024 |
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".