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Record W2401350370 · doi:10.18632/aging.100964

SHIP prevents metastasis

2016· editorial· en· W2401350370 on OpenAlexaff
Gerald Krystal, Melisa J. Hamilton, Kevin L. Bennewith

Bibliographic record

VenueAging · 2016
Typeeditorial
Languageen
FieldMedicine
TopicMyeloproliferative Neoplasms: Diagnosis and Treatment
Canadian institutionsBC Cancer Agency
Fundersnot available
KeywordsMetastasisEnvironmental scienceMedicineInternal medicineCancer

Abstract

fetched live from OpenAlex

The Src-homology-2-containing inositol-5′-phosphatase, SHIP (also known as SHIP1), is a tumor suppressor that negatively regulates the phosphatidylinositol 3-kinase (PI3K) pathway by hydrolyzing the PI3K-generated second messenger phosphatidylinositol-3,4,5-triphosphate (PIP3) to PI-3,4-P2. SHIP expression is restricted primarily to hematopoietic cells, but has also been reported in mesenchymal stem cells (MSCs) and osteoblasts [1]. SHIP levels can be reduced by inactivating mutations, single nucleotide polymorphisms, or miR-155 activity [2], and SHIP expression decreases in the aging MSC compartment of murine bone marrow, skewing hematopoiesis toward production of myeloid cells [1] and potentially leading to the development of myeloproliferative syndromes or myeloid neoplasms with age. It is unknown whether SHIP levels change during the aging process in hematopoietic cells, although aberrant PI3K activity in human neutrophils increases with age, potentially via reduction in SHIP, and negatively impacts neutrophil migration and function [3].

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)0.001
metaresearch head score (Gemma)0.003
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0090.005

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.

Opus teacher head0.018
GPT teacher head0.327
Teacher spread0.309 · 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
GenreEditorial

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

Citations3
Published2016
Admission routes1
Has abstractyes

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