Sustainability in the IVF laboratory: recommendations of an expert panel
Bibliographic record
Abstract
The healthcare industry is a major contributor to greenhouse gas emissions. Assisted reproductive technology is part of the larger healthcare sector, with its own heavy carbon footprint. The social, economic and environmental costs of this collective carbon footprint are becoming clearer, as is the impact on human reproductive health. Alpha Scientists in Reproductive Medicine and the International IVF Initiative collaborated to seek and formulate practical recommendations for sustainability in IVF laboratories. An international panel of experts, enthusiasts and professionals in reproductive medicine, environmental science, architecture, biorepository and law convened to discuss the topics of importance to sustainability. Recommendations were issued on how to build a culture of sustainability in the workplace, implement green design and building, use life cycle analysis to determine the environmental impact, manage cryostorage more sustainably, and understand and manage laboratory waste with prevention as a primary goal. The panel explored whether the industry supporting IVF is sustainable. An example is provided to illustrate the application of green principles to an IVF laboratory through a certification programme. The UK legislative landscape surrounding sustainability is also discussed and a few recommendations on 'Green Conferencing' are offered.
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".