Economic consequences of increased bioenergy demand
Bibliographic record
Abstract
Although wind, hydro and solar are the most discussed sources of renewable energy, countries will need to rely much more on biomass if they are to meet renewable energy targets. In this study, a global forest trade model is used to examine the global effects of expanded demand for wood pellets fired with coal in power plants. Positive mathematical programming is used to calibrate the model to 2011 bilateral trade flows. To assess the impact of increased demand for wood pellets on global forest products, we consider a scenario where demand for wood pellets doubles. Findings indicate that production of lumber and plywood is likely to increase in most of the 20 model regions, but outputs of fibreboard, particleboard and pulp will decline as these products must compete with wood pellets for residual fibre. Ultimately, policies promoting aggressive renewable energy targets cause wood pellet prices to more than double in our scenarios, which could increase the cost of generating electricity to such an extent that, in some regions, electricity producers will continue to use fossil fuels as their primary fuel, while some others might find it worthwhile to rely more on nuclear energy for base load power.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".