Carbon Balance and Management BioMed Central Commentary Improving GHG inventories by regional information exchange: a
Bibliographic record
Abstract
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Background: The Parties to the United Nations Framework Convention on Climate Change (UNFCCC) are required to develop and report a national inventory of greenhouse gases not controlled by the Montreal Protocol. In the Asia region, "Workshops on Greenhouse Gas Inventories in Asia (WGIA) " have been organised annually since 2003 under the support of the government of Japan. WGIAs promote information exchange in the region to support countries' efforts to improve the quality of greenhouse gas inventories. This paper reports the major outcomes of the WGIAs and discusses the key aspects of information exchange in the region for the improvement of inventories. Results: The major outcomes of WGIAs intended to help countries improve GHG inventories, can be summarised as follows: (1) identification of common issues and possible solutions by sector, (2) reporting country inventory practices, and (3) verification of the UNFCCC reporting requirements. Conclusion: The workshops provided the opportunity for countries to share common issues and
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.133 | 0.033 |
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".