Estimating Mill Residue Surplus in Canada: A Spatial Forest Fiber Cascade Modeling Approach
Bibliographic record
Abstract
Abstract The potential development of a Canadian forest-based bioeconomy requires an assessment of both fiber availability and associated marginal supply costs. To a large extent, the bioeconomy is expected to rely on wood fiber made available through primary products, sawnwood, and pulp production processing streams. Therefore, it is important to understand the regional wood fiber flows and mill residue availability through various processing streams. In this study, we developed a spatially explicit Forest Fiber Cascade Model (FCM) to estimate regional fiber flows and availability of untapped residue surplus. The FCM was calibrated to 2013 production levels, and we evaluated the wood fiber cascade through existing forest industry in Canada. The results show that, under current conditions, there is limited availability of surplus mill residues in Canada, especially in the Eastern provinces. It is therefore critical to consider the impacts on regional fiber flows and feedstock availability to the secondary industries when designing feedstock supply strategies and policies for the emerging forest-based industries.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".