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Record W4221010347 · doi:10.1016/j.jacadv.2022.100012

Born to Age: When Adult Congenital Heart Disease Converges With Geroscience

2022· article· en· W4221010347 on OpenAlexafffund
Philip Moons, Ariane Marelli

Bibliographic record

VenueJACC Advances · 2022
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsMcGill University Health Centre
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchFonds Wetenschappelijk OnderzoekHeart and Stroke Foundation of Canada
KeywordsHeart diseaseMedicineDiseasePopulation ageingPopulationPsychological interventionPediatricsIntensive care medicineCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Advances in imaging, catheter-based interventions, congenital heart disease surgery, and clinical management of congenital heart disease (CHD) have yielded a dramatic change in age distribution of the CHD population. This implores clinicians and researchers to gain a better understanding of aging, as this will be the cornerstone to how we plan and manage this rapidly evolving group of patients. In this article, we first review the demographic changes in the CHD population and then describe the systemic complications of disease observed in young patients with CHD, following which we discuss general concepts in aging that may be transferable to the CHD population. Finally, we review inflammation and its potential impact on aging. We provide a new lens on aging in CHD and its functional consequences in CHD, with the goal of stimulating an exchange of knowledge between geroscientists and CHD.

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)0.003
metaresearch head score (Gemma)0.012
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.012
GPT teacher head0.280
Teacher spread0.268 · 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
GenreEmpirical

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

Citations38
Published2022
Admission routes2
Has abstractyes

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