Prenatal and Preimplantation Diagnosis: International Policy Perspectives
Bibliographic record
Abstract
Diagnostic techniques such as prenatal diagnosis (PND) and preimplantation genetic testing (PGT) provide prospective parents with information on phenotypic or genetic traits, on health status, and on the sex of their offspring. The main goal of both PND and PGT is to avoid having a child with a severe genetic condition. This chapter presents an overview of current laws and policies regarding PND, PGT, and sex selection in 16 different countries: Australia, Belgium, Canada, China, France, India, Israel, Japan, the Netherlands, New Zealand, Singapore, Switzerland, South Africa, Spain, United Kingdom, and the United States. In the countries under study, prenatal diagnosis has long become part of the standard of care in pregnancy. The majority of countries under study govern PND through the adoption of professional guidelines and oversight. PGT is ethically acceptable for conditions that are less serious or of lower penetrance due to the respect for reproductive liberty.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.013 | 0.008 |
| Insufficient payload (model declined to judge) | 0.033 | 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".