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Record W2068446093 · doi:10.1055/s-2002-38243

Aortic Carboxypeptidase-Like Protein (ACLP): What is a Protein with a Name Like That Doing in Adipose Tissue?

2002· review· en· W2068446093 on OpenAlexaff
Alexander Sorisky, AnneMarie Gagnon, Kayvan Jasper. Abaiian

Bibliographic record

VenueHormone and Metabolic Research · 2002
Typereview
Languageen
FieldMedicine
TopicCardiovascular Disease and Adiposity
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsAdipose tissueAdipogenesisExtracellular matrixInternal medicineCell biologyEndocrinologyChemistryVascular smooth muscleSmooth muscleBiologyMedicine

Abstract

fetched live from OpenAlex

Introduction Aortic carboxypeptidase-like protein (ACLP) was originally cloned from aortic vascular smooth-muscle cells. It has been chosen as a subject for a hypothesis paper in this current issue of the journal due to its recent identification as a protein that is also expressed in adipose cells. Current data indicate its expression is downregulated during the early phase of the differentiation of fibroblast-like preadipose cells into mature adipose cells (adipogenesis). Remodeling the extracellular matrix (ECM) is a critical early event in adipogenesis, and ACLP may have the potential to interact with matrix components.

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.002
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 head0.065
GPT teacher head0.354
Teacher spread0.289 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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