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Record W2127851311 · doi:10.1158/1078-0432.ccr-07-5134

Regulation of Hematopoietic Stem Cells by the Steel Factor/KIT Signaling Pathway

2008· review· en· W2127851311 on OpenAlexafffund
David G. Kent, Michael R. Copley, Claudia Benz, Brad Dykstra, Michelle B. Bowie, Connie J. Eaves

Bibliographic record

VenueClinical Cancer Research · 2008
Typereview
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsBC Cancer Agency
FundersNational Cancer InstituteCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsHaematopoiesisStem cellBiologyEffectorCell biologySignal transductionHematopoietic stem cellMyeloidStem cell factorCancer researchImmunology

Abstract

fetched live from OpenAlex

Understanding the intrinsic pathways that regulate hematopoietic stem cell (HSC) proliferation and self-renewal responses to external signals offers a rational approach to developing improved strategies for HSC expansion for therapeutic applications. Such studies are also likely to reveal new targets for the treatment of human myeloid malignancies because perturbations of the biological processes that control normal HSC self-renewal divisions are believed to drive the propagation of many of these diseases. Here, we review recent findings that point to the importance of using stringent functional criteria to define HSCs as cells with longterm repopulating activity and evidence that activation of the KIT receptor and many downstream effectors serve as major regulators of changing HSC proliferative and self-renewal behavior during development.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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.

Opus teacher head0.357
GPT teacher head0.507
Teacher spread0.150 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations173
Published2008
Admission routes2
Has abstractyes

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