Prices for a second‐generation biofuel industry in Canada: Market linkages between Canadian wheat and US energy and agricultural commodities
Bibliographic record
Abstract
Abstract The production of biofuels is limited in Canada, but the availability of wheat straw as a second‐generation (i.e., cellulosic) feedstock is an exciting prospect for the future development of a biofuel industry. The future success of such a biofuel industry will depend on future ethanol prices and prices related to wheat straw. These prices are likely to be influenced by markets related to the existing first‐generation ethanol industry in the United States. Therefore, the motivation of this paper is to investigate relationships between Canadian wheat prices and US corn, ethanol, and gasoline prices. We employ a DCC‐MGARCH enhanced VEC model to investigate time‐varying relationships among these markets. Results indicate that there are positive relationships between wheat and corn, ethanol and corn, and wheat and ethanol markets. Our results add to a better understanding of the level of integration between select Canadian agricultural markets and US energy markets. More specifically, the price relationships identified highlight several sources of price risk that may affect the financial success of commercially producing second‐generation ethanol from wheat straw in Canada. This information will be of particular interest to prospective industry investors and policymakers.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".