Bibliographic record
Abstract
Stem cells are defined by their capability for both self-renewal through cell division and for producing a lineage capable of differentiating into one or more specialized cell types. Stem cells are found both in adult tissues and in the developing embryo. While embryonic stem cells are able to differentiate into each and every cell type, adult stem cells are generally only able to form the cell types of the organ from which they originate. Stem cells are essential for the renewal and repair of human tissues and have been at the centre of research into regenerative medicine. They have also emerged as a valuable tool for drug discovery and development. Strong patent protection is a crucial driver of investment into new stem cell technologies. However, their special nature has created a number of uncertainties. In particular, the biological potential of embryonic stem cells to create new human life raised ethical concerns and caused boundaries to be set on the scope of patentability. The bar has been set at different places in the USA, Europe and Canada. Careful assessment of the options for protection in these jurisdictions is necessary in order to manage risk and maximize rewards. This article provides an overview of the patentability of stem cells with a focus on recent developments regarding embryonic, adult and induced pluripotent stem cells.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".