Design and commissioning of a pilot-scale solid state anaerobic digester for the Canadian Prairies
Bibliographic record
Abstract
The Prairie Agricultural Machinery Institute (PAMI) designed and commissioned a pilot-scale solid state digester (SSD) facility at the Termuende Research Ranch near Lanigan, Saskatchewan. The facility includes an airtight containment system and equipment for liquid recirculation, gas collection, metering, compression, and flaring as well as system automation and control instrumentation. A custom gas analyzer was installed to provide continuous and accurate measurements of the methane and carbon dioxide content of the biogas. An environmental screening assessment was completed prior to construction to comply with environmental regulations. All digester components were designed and selected to meet the relevant gas and electrical installation regulations, and the team developed safety guidelines for the facility to ensure the safety of employees, contractors, and visitors. The current configuration of the pilot facility can handle up to 40 tonnes of solid beef manure and straw per batch and approximately 400 tonnes can be digested per year. An expansion reactor can add 200 tonnes to the annual capacity. The addition of gas utilization equipment such as a combined heat and power unit will help demonstrate the use of biogas. The goals of the facility include optimization of operating parameters, demonstration of biogas utilization, and life cycle assessments including the environmental and agronomic impacts of digestate processing and land application. The pilot research facility will also provide information and experience required to design and commission a production scale SSD.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".