MODEL ESTIMATES FOR CONTRIBUTION OF NATURAL AND ANTHROPOGENIC CO2 AND CH4 EMISSIONS INTO THE ATMOSPHERE FROM THE TERRITORY OF RUSSIA, CHINA, CANADA, AND THE USA TO GLOBAL CLIMATE CHANGE IN THE 21ST CENTURY
Bibliographic record
Abstract
Model estimates of the contribution of anthropogenic and natural fluxes of greenhouse gases from the territories of different countries to global climate change in the 21st century under different scenarios of anthropogenic forcing were obtained. Quantitative estimates were made for the effect of changes in regional climatic conditions on the intensity of the greenhouse gas exchange between the atmosphere and natural ecosystems over different time horizons in comparison with anthropogenic emissions. For Russia, China, Canada, and the United States, the CO2 uptake by natural ecosystems in the second half of the 21st century decreases under all scenarios of anthropogenic forcing, with a weakening of the corresponding climate-stabilizing effect. At the same time, the methane emission to the atmosphere by wetlands in the analyzed regions increases significantly in the 21st century according to the model estimates. As a consequence, the cumulative effect of natural fluxes of greenhouse gases into the atmosphere for some regions may accelerate the 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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".