Developing a Catalogue of Environmental Sustainability Tools to Inform Biomedical Engineering Design Education
Bibliographic record
Abstract
Despite the negative impact that the environmental crisis can have on human health, the healthcare sector is a significant contributor of greenhouse gas emissions and air pollution. However, biomedical engineering design has primarily focused on human safety, with limited attention to environmental sustainability. To address this, we conducted a review of tools to support environmental sustainability analysis and proposed how we think they can support biomedical engineering design education. We conducted a literature search to identify available tools and categorized them according to the biomedical engineering design process taught at the University of British Columbia. We found that there was a lack of tools to support sustainability at early design stages, limiting student’s ability to take a proactive approach to sustainable design. Moving forward, we plan to use this review as a reference tool to guide curriculum improvements for biomedical engineering design courses to include a greater focus on environmental sustainability.
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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 | 0.014 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.040 | 0.025 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.010 |
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".