Shares Differences of Greenhouse Gas Emissions Calculated with GTP and GWP for Major Countries
Bibliographic record
Abstract
The global warming potential (GWP) and global temperature potential (GTP) are two common metrics to calculate the CO 2 equivalent of greenhouse gases (GHGs). If the country’s GHG emissions are calculated with GTP instead of GWP, the shares of the EU, USA, Japan, Canada and South Africa rise in the period 1990–2005, and those of Brazil, Australia, China, India, Mexico and Russia decrease. From 2015 to 2030, the projected shares of the EU, USA, Japan and China will increase, but those of Russia, Canada, Australia, India, Mexico and Brazil will decrease. The reduced shares of Brazil and Australia and increased share of the EU might be one of the important reasons that Brazil and Australia suggested to adopt GTP instead of GWP as early as possible, but the EU opposed it. Citation Wang, C.-K., X.-Z. Luo, and H. Zhang, 2013: Shares differences of greenhouse gas emissions calculated with GTP and GWP for major countries. Adv. Clim. Change Res. , 4 (2), doi: 10.3724/SP.J.1248.2013.127.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".