The carbon neutrality assumption for forest bioenergy: A case study for northwestern Ontario
Bibliographic record
Abstract
Minimum break-even and carbon-neutral periods resulting from displacing coal with wood pellets for energy generation at the Atikokan Generating Station (GS) were estimated using forest resource inventory for four forest management units (FMU) in northwestern Ontario. The break-even period was defined as the time since harvest at which the combined greenhouse gas (GHG) benefit of displacing coal with wood pellets and the amount of carbon in the regenerating forest equalled the amount of carbon in the forest had it not been harvested for wood pellets. The carbon-neutral period was defined as the time since harvest at which the amount of carbon in the regenerating forest equalled the amount of carbon in the forest had it not been harvested for wood pellets. Theoretically achievable minimum break-even and carbon-neutral periods were estimated as equal to 18 and 28 years after harvest, respectively. However, for the current forest age structure in the selected FMUs, production of wood pellets required for operation of the Atikokan GS would result in a minimum break-even period of 32 years after harvest. These results must be treated as optimistic since we assumed that all forest was available for harvest for wood pellet production, applied the “best” post-harvest silvicultural regime, and may have underestimated merchantable volume and total carbon stocks in older stands.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".