Toward Guidelines for Research on Human Embryo Models Formed from Stem Cells
Bibliographic record
Abstract
Over the past few years, a number of research groups have reported striking progress on the generation of in vitro models from mouse and human stem cells that replicate aspects of early embryonic development. Not only do these models reproduce some key cell fate decisions but, especially in the mouse system, they also mimic the spatiotemporal arrangements of embryonic and extraembryonic tissues that are required for developmental patterning and implantation in the uterus. If such models could be developed for the early human embryo, they would have great potential benefits for understanding early human development, for biomedical science, and for reducing the use of animals and human embryos in research. However, guidelines for the ethical conduct of this line of work are at present not well defined. In this Forum article, we discuss some key aspects of this emerging area of research and provide some recommendations for its ethical oversight.
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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 | 0.279 | 0.228 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.012 | 0.008 |
| Open science | 0.014 | 0.008 |
| Research integrity | 0.025 | 0.033 |
| Insufficient payload (model declined to judge) | 0.005 | 0.011 |
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".