The forest biorefinery : survival strategy for Canada's pulp and paper sector
Bibliographic record
Abstract
Forest biorefineries were evaluated as a means of reviving the pulp and paper industry in North America. Although advances in genetics, biotechnology, process chemistry and engineering are leading to a new manufacturing concept for converting renewable biomass into valuable fuels and organic chemicals, forest biorefineries will require significant research to reduce and eliminate associated risks. Recent biorefinery initiatives in the United States were reviewed in this article, as well as methodologies for evaluating optimum biorefinery technology practices and pathways for manufacturing financially attractive products. It was observed that existing pulp and paper mills have organized the supply chain for receipt of biomass feedstock, which may make the incremental financial and environmental costs of biorefineries attractive. Various new practices were reviewed, including hemicellulose conversion; the gasification of wood wastes into chemicals; the production of methanol and DME through the gasification of black liquor; and the manufacture of fuel products such as diesel and naphtha. A systematic algorithm for analyzing mill biorefinery opportunities has become the focus of the Natural Sciences and Engineering Research Council Design Chair at the Ecole Polytechnique. It was concluded that biorefineries may succeed as a consequence of increased prices for fuels and chemicals, as well international agreements such as the Kyoto Protocol. However, implementation of the forest biorefinery poses a significant risk at a time when the pulp and paper industry already faces enormous challenges. 1 fig.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".