Financial viability of incorporating different bioenergy systems to an existing sawmill
Bibliographic record
Abstract
The mountain pine beetle has devastated the forests of northern British columbia. As this fibre deteriorates, there will come a time when this timber is no longer economical to harvest for dimension lumber. The government of British Columbia has tried to get new entrants to utilize these damaged stands before the fibre is no longer economical to harvest. The provincial government has also been promoting bioenergy as a source of clean electricity to ensure that British Columbia (B.C.) becomes energy self-sufficient by 2016. The provincial government has also introduced carbon taxes to try and curb the use of fossil fuels. As a result of these government initiatives, the primary objective of this study was to determine if bioenergy systems could be incorporated into an existing sawmill the second objective was to determine under the condions under which bioenergy systems could become financially viable. The data used to determine capital cost of bioenergy systems was from existing publications, which investigated the viability of bioenergy systems using mountain pine beetle damaged timber. An analysis of the data concluded that, under all scenarios bioenergy production as a financial endeavour, is, at best, marginal.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".