Forest biomass for bioenergy as a tool to mitigate climate change: Implications for sustainable forest management in eastern Canada
Bibliographic record
Abstract
Bioenergy produced from residual forest biomass can replace fossil fuels, and its contribution is essential to energy transition. However, its supply costs and selling value hardly ensure its profitability, so it has difficulty competing with other energy sources. In addition, concerns persist about the ecological impacts of forest bioenergy, particularly regarding the carbon cycle, biodiversity and site productivity. Our objective is to identify ways of facilitating the development of the forest bioenergy sector within the sustainable forest management framework of eastern Canada. We reviewed the literature to address the role of forest biomass for bioenergy from an operational, silvicultural and ecological perspective. It emerged that forest bioenergy represents an opportunity for the development of the forestry sector. However, the specifications of the forest biomass to be harvested need to be clarified in order to harmonize its mobilization within the existing industrial ecosystem, while maintaining the ecological functions of forest ecosystems. Integrating biomass harvesting with silvicultural and forest management activities is a key element for developing profitable forest bioenergy business plans.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".