Saskatchewan forest carbon sequestration project
Bibliographic record
Abstract
In 2002 a project in Saskatchewan became the first forest carbon (C) sequestration project to be formally reviewed and approved in Canada under the Greenhouse Gas Emission Trading (GERT) Pilot. GERT concluded that the project will result in real, measurable, verifiable and surplus net sequestration, calculated as C stock changes in the with-project case less C stock changes in the reference (without project) case. The project is a 50-year agreement (2000–2050) in which Saskatchewan Environment sells net C sequestration to the provincial electrical utility Saskatchewan Power Corporation. Net sequestration of 1.6 Mt C is expected to result from the establishment of white spruce plantations on 3300 ha and from forest protection through creation of 206 000 ha of Forest Carbon Reserves. Issues that arose in the review included leakage, the permanence of the sequestered carbon and risk of losses, establishment of the reference case, methodologies for projections of impacts, approaches for sampling and measurements, and accounting methods. GERT established a number of reporting and other conditions to be fulfilled when estimates of actual net sequestration are registered. Future forest C sequestration projects, project reviews and policy development will be able to draw upon the lessons learned from the Saskatchewan project. Key words: carbon sequestration, carbon sequestration projects, Saskatchewan, Greenhouse Gas Emission Reduction Trading Pilot, plantations, forest protection, leakage, permanence, carbon accounting, carbon measurement
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".