Bibliographic record
Abstract
Peatlands cover 12% (1.136 million km2) of the land area of Canada, with perennially frozen peatlands covering 37% of this area and peatlands of the Boreal and Subarctic regions covering 97%. In total, these peatlands contain approximately 147 Gt of soil organic carbon, which is about 56% of the organic carbon stored in all Canadian soils. Climate change predictions suggest that the average annual air temperature in northern Canada will increase 3–5°C by the end of this century. A peatland sensitivity model was used to determine the effect of climate warming on these peatlands. This model predicts that approximately 60% of the area and 56% of the organic carbon mass in all Canadian peatlands will be severely to extremely severely affected by climate change. Although peatlands were affected by climate change in the past, the changes occurred at a slower rate than is predicted for the current change of climate. This accelerated rate of climate change will result in serious degradation of perennially frozen peatlands in the Subarctic and Boreal regions and severe drying of peatlands in the southern portions of the Boreal Region. As a result of these changes, large amounts of carbon in the forms of carbon dioxide (CO2) and methane (CH4) will be released into the atmosphere from these peatlands. This will further accelerate climate warming.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".