Bibliographic record
Abstract
A new international agreement on the conservation and sustainable use of marine biodiversity of areas beyond national jurisdiction (BBNJ) was adopted and subsequently opened for signature in September 2023. Yet on average, recent multilateral environmental agreements (MEAs) have taken over four years to move from signature to entry into force, while ocean-focused MEAs have taken nearly twice as long. Rapid ratification of the BBNJ Agreement is crucial for multiple reasons, not least to achieve the Kunming-Montreal Biodiversity Framework target for 30% of the marine environment to be protected by 2030. It is also vital to fulfill the Agreement’s stated ambition to contribute to a just and equitable future for humankind, considering today’s unprecedented expansion of commercial activities into the ocean.
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 | 0.110 | 0.185 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.048 | 0.033 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.029 | 0.021 |
| Insufficient payload (model declined to judge) | 0.057 | 0.046 |
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".