Gasification/Cogeneration Using MSW Residuals and Biomass
Bibliographic record
Abstract
The City of Edmonton presently collects and processes about 230,000 tonnes of municipal solid waste (MSW) and recyclables per year at the composting and materials recovery facilities located at the Edmonton Waste Management Centre. Over 60% of the waste materials that are brought to the facilities are recycled and composted. Remaining residuals from both the composting and materials recovery facilities have little value in terms of being further recycled and are currently being landfilled. The residuals do have a significant calorific value and have the potential to produce enough electricity to provide 100% of the power and heating for facilities at the Edmonton Waste Management Centre (EWMC), with remaining energy for adjacent developments. The City is considering advanced thermal treatment (not conventional incineration) of the residual waste (after recycling and composting) as a way to close the loop in waste management in terms of minimizing waste materials that are landfilled and reducing the net energy requirement for waste processing and disposal to nil. Other renewable biomass waste streams (e.g.: wood or agricultural waste) could complement operation of the facility and make it more economically viable (economies of scale). There are also other environmental benefits such as reductions in the overall greenhouse gas (GHG) and other harmful emissions by displacement of fossil fuel as an energy source.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".