Bibliographic record
Abstract
The most common human cell-based therapy applied today is hematopoietic stem cell (HSC) transplantation. HSCs can be defined by two essential properties: self-renewal and multilineage hematopoietic differentiation. These combined HSC properties allow them to differentiate into all blood cell types (multilineage) in a sustained manner for the lifetime of the animal, which requires their ability to make cellular copies of themselves (self-renewal). These features can be tested by transplantation from donor to recipient and provide a functional basis to define and identify HSCs. Currently, human bone marrow (BM), mobilized peripheral blood, and umbilical cord blood (CB) represent the major sources of transplantable HSCs, but their availability for use is limited by both quantity and compatibility. Although increasing evidence suggests that somatic HSCs can be expanded to meet current needs, their in vivo potential is concomitantly compromised after ex vivo culture. Pluripotent human embryonic stem cells (hESCs) may provide an alternative. hESCs possess indefinite proliferative capacity in vitro, and have been shown to differentiate into the hematopoietic cell fate, giving rise to erythroid, myeloid, and lymphoid lineages using a variety of differentiation procedures. In most cases, hESC-derived hematopoietic cells show similar clonogenic progenitor capacity and primitive phenotype to somatic sources of hematopoietic progenitors, but possess limited in vivo repopulating capacity when transplanted into immunodeficient mice. Although this suggests HSC function can be derived from hESCs, the efficiency and quality of these cells must be characterized using surrogate models for potential clinical applications.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".