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Record W2148913389 · doi:10.1212/wnl.0b013e318200d822

Endothelial progenitor cells and vascular disease

2010· letter· en· W2148913389 on OpenAlexafffund
Askar Mohammad, Ashfaq Shuaib

Bibliographic record

VenueNeurology · 2010
Typeletter
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAngiogenesis and VEGF in Cancer
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsProgenitor cellMedicineMyocardial infarctionStroke (engine)Vascular diseaseCoronary artery diseaseEndothelial progenitor cellCardiologyDiseaseInternal medicineEndothelial stem cellInfarctionProgenitorIschemiaStem cellBiologyIn vitroCell biology

Abstract

fetched live from OpenAlex

Endothelial progenitor cells (EPCs) were initially described in 1997, though their properties and roles are still being investigated and debated. Their core characteristics were identified as circulating cells displaying a variety of cell surface proteins thought to be endothelial specific, the ability to grow in culture, and the ability to localize and promote vascular growth at sites of ischemia.1 Very soon thereafter, studies suggested an inverse relationship between the number of circulating EPCs and vascular risk factors in patients with stable ischemic heart disease2 and, later, in those with acute or stable stroke.3 Subsequent reports suggested that the use of statins could increase EPC numbers in patients with stable coronary artery disease, though this observation was not confirmed in a larger randomized trial.4 Other data suggested that infusion of EPCs after an acute myocardial infarction could result in improvement in cardiac function and decreased mortality.5 The initial excitement, not surprisingly, prompted numerous investigations on EPCs. However, despite 13 years having passed since the landmark article in Science ,1 and having done further, more detailed, analyses on EPCs, we are still …

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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.006
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0030.002

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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
GenreCommentary

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
Published2010
Admission routes2
Has abstractyes

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