Rollen för negativa utsläpp för att bidra till att klara Parisavtalets långsiktiga mål
Bibliographic record
Abstract
This report delves into the multifaceted dimensions of carbon dioxide removal methods. The report discusses the role of carbon dioxide removal methods in contributing to attaining the long-term goal of the Paris Agreement and investigates best practices in the implementation of the collaborative instruments under Article 6 for their incentivisation and scaling. The present climate policy and actual decision-making are still centred on achieving net-zero carbon emissions but the long-term challenge is the inevitable reversal of the overshoot, requiring carbon removal to outpace residual emissions, leading to net negative emissions globally. The report discusses the need to assign responsibility for climate overshoot reversal in order to guarantee the viability of a global net-negative GHG economy. The report analyses and proposes ways to address risks associated with carbon removal, including mitigation deterrence, that carbon removed from the atmosphere might be re-released, carbon-leakage effects, and challenges related to monitoring mitigation outcomes. It offers recommendations based on these deliberations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.248 | 0.124 |
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".