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Record W2986983976 · doi:10.1042/cs20190866

A tangled tale of microRNA and cardiac fibrosis

2019· letter· en· W2986983976 on OpenAlex
Mark Chandy

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Science · 2019
Typeletter
Languageen
FieldMedicine
TopicCardiac Fibrosis and Remodeling
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExtracellular matrixMyofibroblastFibrosisCardiac fibrosisFibroblastWound healingmicroRNARegeneration (biology)MedicineHeart failurePathologicalPressure overloadPathologyCancer researchBioinformaticsCell biologyCardiologyBiologyCardiac hypertrophySurgery

Abstract

fetched live from OpenAlex

Cardiac fibrosis is important for wound healing, regeneration and producing the extracellular matrix (ECM) that provides the scaffold for cells. In pathological situations, fibroblasts are activated and remodel the ECM. In volume 133, issue 17 of Clinical Science, Yang et al. discovered that the miR-214-3p/NLRC5 axis is important for fibroblast-to-myofibroblast transition (FMT) and ECM remodelling in a pressure overload model of fibrosis [Clin. Sci. (2019) 133(17), 1845-1856]. This discovery helps to explain the complicated regulation of cardiac fibrosis. It also underscores the need for more investigation into the mechanisms of cardiac fibrosis to develop better diagnostic modalities and therapeutic options in heart failure.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: none
Teacher disagreement score0.289
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.346
Teacher spread0.307 · 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