Bioresource Engineering Curriculum and Reform at McGill University, Montreal, Canada
Bibliographic record
Abstract
The Bioresource Engineering Programme at McGill University is run by the department of the same name on the Macdonald Campus, in Ste-Anne-de-Bellevue near Montreal, Canada. The programme began as the Manual Training Programme in 1910, shortly after the founding of the campus. The organisation of the programme was continually modernised as it grew over the subsequent century. In the late 1960s it was accredited as a professional degree programme in Agricultural Engineering and a graduate programme was instituted. The undergraduate curriculum encompassed the traditional areas of agricultural engineering such as irrigation and drainage, soil and water management, farm structures, and power and machinery. In 2003, in the face of a wave of closures of similar programmes across North America, the department was rebranded as Bioresource Engineering. The current, expanded programme is structured according to three streams: the production of biomass, the processing of commodities into consumer products, and the management of the environmental impacts of those activities. The curriculum trains engineers who can help society transition away from a linear economy dependent on fossil energy and nonrenewable resources to a circular, regenerative economy that leverages renewable energy and biological resources.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.129 | 0.016 |
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".