The Zero Emissions Commitment and climate stabilization
Bibliographic record
Abstract
How do we halt global warming? Reaching net zero carbon dioxide (CO 2 ) emissions is understood to be a key milestone on the path to a safer planet. But how confident are we that when we stop carbon emissions, we also stop global warming? The Zero Emissions Commitment (ZEC) quantifies how much warming or cooling we can expect following a complete cessation of anthropogenic CO 2 emissions. To date, the best estimate by the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report is zero change, though with substantial uncertainty. In this article, we present an overview of the changes expected in major Earth system processes after net zero and their potential impact on global surface temperature, providing an outlook toward building a more confident assessment of ZEC in the decades to come. We propose a structure to guide research into ZEC and associated changes in the climate, separating the impacts expected over decades, centuries, and millennia. As we look ahead at the century billed to mark the end of net anthropogenic CO 2 emissions, we ask: what is the prospect of a stable climate in a post-net zero world?
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".