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Enhanced Cardiomyocyte NLRP3 Inflammasome Signaling Promotes Atrial Fibrillation

2018· article· en· W2804559696 on OpenAlexaff
Chunxia Yao, Tina Veleva, Larry Scott, Shuyi Cao, Luge Li, Gong Chen, Prince Jeyabal, Xiaolu Pan, Katherina M. Alsina, Issam Abu-Taha, Shokoufeh Ghezelbash, Corey Reynolds, Ying H. Shen, Scott A. LeMaire, Wilhelm Schmitz, Frank U. Müller, Ali El‐Armouche, N. Tony Eissa, Christine Beeton, Stanley Nattel, Xander H.T. Wehrens, Dobromir Dobrev, Na Li

Bibliographic record

VenueCirculation · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsMontreal Heart Institute
FundersNational Institute of General Medical SciencesNational Human Genome Research InstituteNational Heart, Lung, and Blood Institute
KeywordsMedicineInflammasomeAtrial fibrillationCardiologyInternal medicineSignal transductionCell biologyInflammation

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.240
Teacher spread0.230 · 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 designObservational
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

Citations641
Published2018
Admission routes1
Has abstractyes

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