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Record W2811098386 · doi:10.1183/16000617.0033-2018

Matrix abnormalities in pulmonary fibrosis

2018· review· en· W2811098386 on OpenAlexaff
Chandak Upagupta, Chiko Shimbori, Rahmah Alsilmi, Martin Kolb

Bibliographic record

VenueEuropean Respiratory Review · 2018
Typereview
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMyofibroblastExtracellular matrixIdiopathic pulmonary fibrosisTransforming growth factorPulmonary fibrosisMedicineFibrosisCell biologyFibroblastPhenotypeMatrix (chemical analysis)PathologyMatrix metalloproteinaseCancer researchLungImmunologyBiologyChemistryInternal medicineCell culture

Abstract

fetched live from OpenAlex

Idiopathic pulmonary fibrosis (IPF) is a devastating, progressive disease, marked by excessive scarring, which leads to increased tissue stiffness, loss in lung function and ultimately death. IPF is characterised by progressive fibroblast and myofibroblast proliferation, and extensive deposition of extracellular matrix (ECM). Myofibroblasts play a key role in ECM deposition. Transforming growth factor (TGF)-β1 is a major growth factor involved in myofibroblast differentiation, and the creation of a profibrotic microenvironment. There is a strong link between increased ECM stiffness and profibrotic changes in cell phenotype and differentiation. The activation of TGF-β1 in response to mechanical stress from a stiff ECM explains some of the influence of the tissue microenvironment on cell phenotype and function. Understanding the close relationship between cells and their surrounding microenvironment will ultimately facilitate better management strategies for IPF.

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 score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.003

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 head0.066
GPT teacher head0.369
Teacher spread0.303 · 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

Citations277
Published2018
Admission routes1
Has abstractyes

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