Feasibility Of Renewable Energy For Rural Community Capacity Building In Value Added Businesses - A Focus On Waste To Energy Technologies In Small Abattoirs
Bibliographic record
Abstract
Since the entry of multinationals in the Canadian beef packing industry and the discovery of the bovine spongiform encephalopathy in Canada, small abattoirs have been hard hit and are slowly starting to fade out across the Province of Alberta. Value added industries are crucial to the economic sustainability of communities dependent on primary sectors and with the use of waste to energy technologies could become sustainable. By evaluating the feasibility of waste to energy technologies in abattoir of rural Alberta, it was found that gasification technology satisfied the requirements for energy production using slaughter waste. Due to the small size of rural abattoirs and the need for waste to make this technology feasible, a zone with multiple abattoirs and considerable agricultural biomass to use along the abattoir waste was delineated. Although the technology comes at a high price, it was estimated that the payback time through savings incurred by the use of gasification technology would be 10.17 years with an average useful life of 4.83 years.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".