Positioning anaerobic digestion systems in the swine sector in Quebec: a technical and economic study
Bibliographic record
Abstract
The goal of this study was to position on-farm anaerobic digester using technical and economic analyses based on scenarios adapted to the regulatory and economic context of the swine sector in the province of Quebec where there is so little experience with this type of process so far. For the present study, three scenarios were selected in order to represent, as closely as possible, operating conditions in this swine sector to perform this global technical and economic analysis. An economic analysis was carried out to determine the profitability of each scenario. Preliminary results indicate that the profitability of this type of project under conditions prevailing in Quebec is hardly profitable. If thermal use of biogas is considered, the challenge is to produce biogas at a cost lower than that of natural gas ($0.46/m 3 of methane at 0 o C and 1 atm) whereas the best-case scenario in the present study shows a production cost of $0.97/m 3 of methane. Different incomes, other than biogas sale, can improve the profitability of the scenarios. If biogas is used to generate electricity, the issue at stake is to produce electricity at a price of less than $0.0746/kWh (Hydro-Quebec, 2010) when it is used directly at the farm, or to obtain a price of $0.112/kWh in cases where it can be resold on the electrical grid by tendering through Hydro-Quebec. These market prices are significantly lower than the electricity production cost laid out in the most realistic scenario ($0.46/kWh).
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".