Exploring the potential of upcycling craft brewers spent grain in Winnipeg, Manitoba
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Food upcycling is a circular economy method of reducing food waste by adding value to foods that conventionally would have gone to waste. This project explores the potential of upcycling brewers spent grain (BSG) to human food products in Winnipeg, MB to think global and act local, primarily considering The Paris Agreement, The United Nations 17 Sustainable Development Goals, and planetary boundaries. Data was derived from a comprehensive literature review, a website review of 1165 unique Canadian craft breweries, 168 responses to a Canada-wide craft brewer survey, and 12 semi-structured interviews. The data analysis shows that with the current brewer interest, there is sufficient spent grain volumes to upcycle at small scales locally and suggests that large scale/industrial supply is possible with the participation of all local craft breweries. The suggested framework pick-up route would lower spent grain transportation emissions of all local breweries by 25-50%. The final recommendation report concludes that the majority of local spent grain currently goes to animal feed, but Winnipeg does in fact have potential to upcycle BSG locally while minimizing or removing barriers to upcycle for all affected parties, while increasing sustainable operations of local food and beverage companies.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it