Other effective area-based conservation measures (OECMs) for the conservation and wise use of wetlands
Bibliographic record
Abstract
The role and importance of Other effective area-based conservation measures (OECMs) have been formally acknowledged internationally by Contracting Parties to the Convention on Biological Diversity (CBD) through Decision 14/8 (which includes OECM identification criteria) and supplemented with international best practice best guidance from IUCN on identifying, recognizing, monitoring and reporting on OECMs, including an OECM site-selection tool. This Briefing Note aims to assist Contracting Parties to the Convention on Wetlands in the identification and use of OECMs as a mechanism to further the conservation and wise use of wetlands and contribute to commitments under the Convention (including its Strategic Plan), Target 3 (and other targets) of the Kunming-Montreal Global Biodiversity Framework (KM-GBF), and in other Multilateral Environmental Agreements and other international processes, e.g., the Sustainable Development Goals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".