Bibliographic record
Abstract
In vitro maturation of oocytes is a safe and effective treatment offered in some fertility centers for assisted reproduction, where immature oocytes are retrieved from unstimulated ovaries. Therefore, the procedure avoids ovarian stimulation with expensive gonadotropins, side effects of the medications, and risks such as ovarian hyperstimulation syndrome. Added advantages are reduced frequency of monitoring scans and shorter treatment regimen compared with in vitro fertilization. The candidates initially considered were women with polycystic ovaries having multiple antral follicles, but the indications are widening to include women with primarily poor quality embryos in repeated cycles and poor responders to stimulation. The two new applications for in vitro maturation we are now successfully implementing at McGill Reproductive Center are for oocyte donors and for fertility preservation, especially in women with cancer who are undergoing gonadotoxic therapy. In young women without partners needing this treatment for fertility preservation, it is combined with vitrification of the oocytes. We have achieved a 38% clinical pregnancy rate per cycle in women having IVM for infertility treatment up to the age of 35 years, and 50% clinical pregnancy rate per cycle in recipients of IVM egg donation.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.005 |
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".