Bibliographic record
Abstract
Two emissions trading systems ( ETS ) are linked if a participant in one system can use an allowance or a credit issued by either system for compliance. Linking ETS offers a number of potential benefits including, lower overall compliance cost, price protection, greater liquidity in the allowance market, and reduced emissions leakage. It is useful to distinguish: (a) A unilateral link—one ETS accepts the allowances of another ETS for compliance purposes, but not vice versa. Any link to an offset system, such as the Clean Development Mechanism ( CDM ), is a unilateral link for the ETS that accepts those credits. (b) A bilateral link—each ETS accepts the allowances of the other ETS for compliance purposes. Another way to implement a bilateral link is to adopt a common compliance instrument. The European Union ETS ( EU ETS ) has a single compliance instrument—the EU allowance—that is used in all 31 participating countries. Several national and subnational jurisdictions have established an ETS for one or more greenhouse gases ( GHGs ). Some of these ETS also issue offset credits for GHG emission reductions achieved by specified sources. In addition, the international CDM and Joint Implementation ( JI ) mechanisms issue offset credits for GHG emission reductions. Most ETS have established unilateral links, mainly to the CDM and JI , but also to other ETS . Apart from the systems that are part of the EU ETS and Regional Greenhouse Gas Initiative ( RGGI ) only one bilateral link, between the California and Quebec ETS , has been established. This study summarizes the experience with linking GHG ETS . WIREs Energy Environ 2016, 5:246–260. doi: 10.1002/wene.191 This article is categorized under: Energy and Climate > Economics and Policy Energy and Climate > Systems and Infrastructure Energy Policy and Planning > Climate and Environment
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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 | 0.027 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.003 |
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".