Bibliographic record
Abstract
As the gavel came down at 3:18 a.m. at the United Nations Environment Programme (UNEP) meeting to create a global treaty to end plastic pollution , the room breathed an exhausted sigh of relief. For the first time, the negotiating committee had agreed on a plan for work to be done before the next meeting on the treaty, scheduled for a scant 7 months from now. Along with over 2,500 participants from 170 countries, a sense of urgency filled the halls at the Shaw Center, in Ottawa, Ontario, for the fourth intergovernmental negotiating committee meeting (INC-4) the last week of April. The next meeting, INC-5, is also the final one, since the 2022 mandate is that negotiations on the treaty be done by the end of 2024. Early in the week, participants poured in past a 6 m tall sculpture of a faucet spewing discarded plastic and images splashed across
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.002 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.163 | 0.064 |
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".