The essential carbon service provided by northern peatlands
Bibliographic record
Abstract
Northern peatlands have cooled the global climate by accumulating large quantities of soil carbon (C) over thousands of years. Maintaining the C sink function of these peatlands and their immense long‐term soil C stores is critical for achieving net‐zero global carbon dioxide (CO2) emissions by 2050 to mitigate climate warming. One‐quarter of the world’s northern peatlands are in Canada, with these mostly intact ecosystems providing a global C service that is increasingly recognized as a critical part of nature‐based solutions to combat climate change. However, land‐use change and other disturbances threaten these globally important stores of “irrecoverable C” (that is, soil C lost to disturbance that will take centuries to recover). Inadequate policy safeguards to avoid conversion and degradation, and the limited quantification and reporting of peatland greenhouse‐gas emissions and removals, increase the vulnerability of these peatlands. Targeted policies from local to global scales will be needed for improved decision making and incentivizing long‐term C management of northern peatlands.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".