Bibliographic record
Abstract
Hematopoietic stem cell (HSC) research took hold in the 1950s with the demonstration that intravenously injected bone marrow cells can rescue irradiated mice from lethality by reestablishing blood cell production. Attempts to quantify the cells responsible led to the discovery of serially transplantable, donor-derived, macroscopic, multilineage colonies detectable on the spleen surface 1 to 2 weeks posttransplant. The concept of self-renewing multipotent HSCs was born, but accompanied by perplexing evidence of great variability in the outcomes of HSC self-renewal divisions. The next 60 years saw an explosion in the development and use of more refined tools for assessing the behavior of prospectively purified subsets of hematopoietic cells with blood cell-producing capacity. These developments have led to the formulation of increasingly complex hierarchical models of hematopoiesis and a growing list of intrinsic and extrinsic elements that regulate HSC cycling status, viability, self-renewal, and lineage outputs. More recent examination of these properties in individual, highly purified HSCs and analyses of their perpetuation in clonally generated progeny HSCs have now provided definitive evidence of linearly transmitted heterogeneity in HSC states. These results anticipate the need and use of emerging new technologies to establish models that will accommodate such pluralistic features of HSCs and their control mechanisms.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".