Evaluation of infrastructure requirements for a lignocellulosic ethanol fuelled light-duty fleet in Ontario
Bibliographic record
Abstract
Prospects for lignocellulosic ethanol industry from grasses and agricultural residues in Ontario were evaluated. The amount of land that could potentially be used for growing grasses was estimated, under various assumptions. The amount of agricultural residues that might be collected in the province was estimated. The maximum total amount of lignocellulosic ethanol that can be produced domestically in Ontario under the most optimistic long-term future scenario was found to be 2.61 Billion litres, which is about 20% of the demand for E85 ethanol blend in the province. The areas with the highest potential yield of biomass were identified and possible locations of ethanol conversion plants were proposed. A linear optimization model for the calculation of the total transportation cost of ethanol from the plants to the demand centers was developed, and the total cost of lignocellulosic ethanol production was estimated to range from $0.51 to $0.55 per litre.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".