Human germline genome editing is illegal in Canada, but could it be desirable for some members of the rare disease community?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Human germline genome editing may prove to be especially poignant for members of the rare disease community, many of whom are diagnosed with monogenic diseases. This community lacks broad representation in the literature surrounding genome editing, notably in Canada, yet is likely to be directly affected by eventual clinical applications of this technology. Although not generalizable, the literature does offer some commonalities regarding the experiences of rare disease patients. This manuscript seeks to contribute to the search for broader societal dialogue surrounding human germline genome editing by exploring some of those commonalities that comfort the notion that CRISPR may hold promise or be desirable for some members of this community. We first explore the legal and policy context surrounding germline genome editing, focusing closely on Canada, then provide an overview of the common challenges experienced by members of the rare disease community, and finally assess the opportunities of germline genome editing vis-à-vis rare disease as we advocate for the need to more actively engage with the community in our search for public engagement.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it