Stem cell-based embryo models: The 2021 ISSCR stem cell guidelines revisited
Bibliographic record
Abstract
Human stem cell-based embryo models (SCBEMs) are a research technology with the potential to facilitate our understanding of human embryogenesis, improve assisted reproductive technology outcomes, elucidate the causes of early pregnancy failure, and provide a clearer understanding of the developmental origins of disease. Given that human SCBEMs are designed to model specific phenotypic features and developmental processes of human embryos, they raise distinct concerns from other stem cell models, such as organoids. The International Society for Stem Cell Research (ISSCR) Guidelines for Stem Cell Research and Clinical Translation, published in 2021, made recommendations for research oversight of SCBEMs and established different categories of review based on involvement of embryonic and extraembryonic lineages. However, recent progress has enabled unexpected ways to create increasingly complex models, as well as more efficient means of doing so without including all major extraembryonic lineages. A working group was tasked by the ISSCR executive to undertake a thorough reexamination of the guidelines in the light of these advances. The three main recommendations of the working group are that all research involving organized 3-dimensional human SCBEMs (1) should be subject to appropriate review, (2) must have a clear scientific rationale, and (3) must be subject to limited timelines. The proposed modifications to the ISSCR guidelines are intended to bring more clarity to the field, help guide the deliberations of researchers, oversight committees and other relevant stakeholders, and ensure continued public confidence.
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 | 0.191 | 0.179 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.012 | 0.008 |
| Research integrity | 0.032 | 0.029 |
| 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".