MétaCan
Menu
Back to cohort
Record W4401560014 · doi:10.1201/9780429150111-10

Bioresource Engineering Curriculum and Reform at McGill University, Montreal, Canada

2024· book-chapter· en· W4401560014 on OpenAlexaboutno aff
O. Clark, Valérie Orsat

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumLibrary sciencePolitical scienceEngineering ethicsSociologyMathematics educationMedia studiesEngineeringPedagogyComputer sciencePsychology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.132
Teacher spread0.129 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicBiomedical and Engineering EducationFrench-language works237,207