DONATING FRESH VERSUS FROZEN EMBRYOS TO STEM CELL RESEARCH: IN WHOSE INTERESTS?
Bibliographic record
Abstract
Some stem cell researchers believe that it is easier to derive human embryonic stem cells from fresh rather than frozen embryos and they have had in vitro fertilization (IVF) clinicians invite their infertility patients to donate their fresh embryos for research use. These embryos include those that are deemed 'suitable for transfer' (i.e. to the woman's uterus) and those deemed unsuitable in this regard. This paper focuses on fresh embryos deemed suitable for transfer - hereafter 'fresh embryos'- which IVF patients have good reason not to donate. We explain why donating them to research is not in the self-interests specifically of female IVF patients. Next, we consider the other-regarding interests of these patients and conclude that while fresh embryo donation may serve those interests, it does so at unnecessary cost to patients' self-interests. Lastly, we review some of the potential barriers to the autonomous donation of fresh embryos to research and highlight the risk that female IVF patients invited to donate these embryos will misunderstand key aspects of the donation decision, be coerced to donate, or be exploited in the consent process. On the basis of our analysis, we conclude that patients should not be asked to donate their fresh embryos to stem cell research.
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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 | 0.059 | 0.098 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".