Chapter 3. Assessing progress towards meeting major international objectives related to nature and nature's contributions to people
Bibliographic record
Abstract
This document contains the draft Chapter 3 of the IPBES Global Assessment on Biodiversity and Ecosystem Services. Governments and all observers at IPBES-7 had access to these draft chapters eight weeks prior to IPBES-7. Governments accepted the Chapters at IPBES-7 based on the understanding that revisions made to the SPM during the Plenary, as a result of the dialogue between Governments and scientists, wouldbe reflected in the final Chapters.IPBES typically releases its Chapters publicly only in their final form, which implies a delay of several months post Plenary. However, in light of the high interest for the Chapters, IPBES is releasing the six Chapters early (31 May 2019) in a draft form. Authors of the reports are currently working to reflect all the changes made to the Summary for Policymakers during the Plenary to the Chapters, and to perform final copyediting.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.054 | 0.025 |
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".