Bibliographic record
Abstract
Ms. F and Mr. G are trying to have a child. They have been having sexual intercourse approximately three times a week for the past year, and daily around the time when Ms. F thinks she is ovulating. They are both 38 years old. Ms. F has had regular menstrual cycles up to the last three months, in which she has had only two. They are worried they have delayed starting a family too long and will not be able to afford the expensive fertility treatment they may require at Ms. F's age. They have questions regarding the success of in vitro fertilization and the possibility of having twins or triplets. What is assisted reproduction? Assisted reproduction enables the deliberate manipulation of the processes and materials of human reproduction outside of sexual intercourse. In describing the practices that constitute assisted reproduction, it must be understood that all such practices are embedded with ethical issues, whether standard therapies such as ovulation induction (Messinis, 2005), insemination with donor sperm (Daniels et al ., 2006), and in vitro fertilization (IVF) (Steptoe and Edwards, 1978); emerging practices such as pre-implantation genetic diagnosis (PGD) (Handyside, 1990; Nisker and Gore-Langton, 1995); or practices prohibited under law in many countries, such as the purchase or bartering of oocytes (Gurmankin, 2001; Nisker, 1996, 1997, 2001). Ovulation induction through clomiphene citrate has been practiced for over 30 years (Messinis, 2005).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.263 | 0.170 |
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".