The Montreal Criteria for the Ethical Feasibility of Uterine Transplantation
Bibliographic record
Abstract
Absolute uterine factor infertility (UFI) refers to the refractory causes of female infertility stemming from the anatomical or physiological inability of a uterus to sustain gestation. Today, uterine factor infertility affects 3-5% of the population. Traditionally, although surrogacy and adoption have been the only viable options for females affected by this condition, the uterine transplant is currently under investigation as a potential medical alternative for women who desire to go through the experience of pregnancy. Although animal models have shown promising results, human transplantation cases have only been described in case reports and a successful transplant leading to gestation is yet to occur in humans. Notwithstanding the intricate medical and scientific complexities that a uterine transplant places on the medical minds of our time, ethical questions on this matter pose a similar, if not greater, challenge. In light of these facts, this article attempts to present the ethical issues in the context of experimentation and standard practice which surround this controversial and potentially paradigm-altering procedure; and given these, introduces "The Montreal Criteria for the Ethical Feasibility of Uterine Transplantation", a set of proposed criteria required for a woman to be ethically considered a candidate for uterine transplantation.
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 | 0.053 | 0.121 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".